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Formats:
json
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Tags:
authorship-strategy
ai-era-authenticity
attribution-diffusion
doi-federation
concept-doi
zenodo
License:
@id string | @type unknown | name string | description string | isBasedOn string | mainEntity string | creator dict | license string | inLanguage list | keywords list | siblingOf unknown | downstreamOf unknown | extends unknown | instantiatedBy unknown | alternateName unknown | author unknown | sameAs unknown | url string | identifier string | isPartOf string | definesConcept list | citation list | vocabularyDisjoint string | hasPart string | composedOf list | recordedIn string | subjectOf string | axisPosition int64 | covaresWith list | groundedIn list | layerOrdinal int64 | pairedWith string | appliesTo string | derivesFrom string | datePublished string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
https://github.com/shimo4228/authorship-strategy#knowledge-graph | [
"Dataset",
"CreativeWork"
] | Authorship Strategy Knowledge Graph | Canonical machine-readable relationship map for the Authorship Strategy research line. Encodes the three-axis inversion (scarcity to diffusion, exclusivity to derivation, enclosure to openness), the four-layer framework (Authenticity, Attribution Diffusion, Idea vs Scaffold, Tactics), the twenty tactical ADRs (identifi... | https://github.com/shimo4228/authorship-strategy | https://doi.org/10.5281/zenodo.20263316 | {
"@id": "https://orcid.org/0009-0002-6168-4162"
} | https://opensource.org/licenses/MIT | [
"en",
"ja"
] | [
"authorship strategy",
"AI-era authenticity",
"attribution diffusion",
"three-axis inversion",
"four-layer framework",
"idea vs scaffold",
"concept DOI",
"DOI federation",
"cross-platform federation",
"ORCID enrichment",
"audience-driven localization",
"LLM-mediated diffusion",
"dual entry p... | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
https://orcid.org/0009-0002-6168-4162 | "Person" | Tatsuya Shimomoto | null | null | null | null | null | null | null | null | null | null | null | [
"shimo4228",
{
"@value": "下本竜也",
"@language": "ja"
}
] | null | [
"https://github.com/shimo4228",
"https://orcid.org/0009-0002-6168-4162",
"https://www.wikidata.org/wiki/Q140090100",
"https://scholar.google.com/citations?user=56_p8vEAAAAJ",
"https://huggingface.co/Shimo4228",
"https://www.linkedin.com/in/%E7%AB%9C%E4%B9%9F-%E4%B8%8B%E6%9C%AC-bb9b793a4",
"https://zenn.... | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy | [
"ResearchLine",
"ScholarlyArticle"
] | Authorship Strategy | A normative framework, tactical catalog, and empirical baseline for authorship strategy under AI-mediated diffusion. The framework rests on a three-axis inversion and a four-layer judgment stack; the tactical catalog records twenty decisions extracted from operating a four-repository DOI-registered research ecosystem. | null | null | {
"@id": "https://orcid.org/0009-0002-6168-4162"
} | https://opensource.org/licenses/MIT | [
"en",
"ja"
] | null | [
"https://doi.org/10.5281/zenodo.19200726",
"https://doi.org/10.5281/zenodo.19212118",
"https://doi.org/10.5281/zenodo.19652013",
"https://doi.org/10.5281/zenodo.20262112"
] | null | null | null | [
{
"@value": "Authorship Strategy",
"@language": "en"
},
{
"@value": "著者戦略",
"@language": "ja"
},
"AS"
] | null | [
"https://doi.org/10.5281/zenodo.20263316",
"https://www.wikidata.org/wiki/Q140090190"
] | https://github.com/shimo4228/authorship-strategy | 10.5281/zenodo.20263316 | https://github.com/shimo4228/shimo4228 | [
"https://github.com/shimo4228/authorship-strategy#concept/three-axis-inversion",
"https://github.com/shimo4228/authorship-strategy#concept/four-layer-framework",
"https://github.com/shimo4228/authorship-strategy#concept/authenticity",
"https://github.com/shimo4228/authorship-strategy#concept/attribution-diffu... | [
"https://arxiv.org/abs/2602.06718",
"https://arxiv.org/abs/2604.25707",
"https://arxiv.org/abs/2603.09296",
"https://arxiv.org/abs/2402.12261",
"https://arxiv.org/abs/2510.08506"
] | https://doi.org/10.5281/zenodo.19652013 | https://github.com/shimo4228/authorship-strategy/blob/main/docs/implementations.md | null | null | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/three-axis-inversion | "Concept" | Three-Axis Inversion | The structural claim that twentieth-century authorship strategy and AI-era authorship strategy invert on three co-varying axes: value source (scarcity to diffusion), validation mechanism (exclusivity to derivation), network effect (enclosure to openness). The three axes co-vary; a strategy mixing axes is internally inc... | null | null | null | null | null | null | null | null | null | null | [
{
"@value": "Three-Axis Inversion",
"@language": "en"
},
{
"@value": "3 軸反転",
"@language": "ja"
},
{
"@value": "三轴反转",
"@language": "zh"
}
] | null | null | null | null | null | null | null | null | null | [
"https://github.com/shimo4228/authorship-strategy#concept/scarcity-to-diffusion-axis",
"https://github.com/shimo4228/authorship-strategy#concept/exclusivity-to-derivation-axis",
"https://github.com/shimo4228/authorship-strategy#concept/enclosure-to-openness-axis"
] | https://github.com/shimo4228/authorship-strategy/blob/main/docs/thesis.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/four-layer-framework | "Concept" | Four-Layer Framework | The operational structure of judgment that follows from the three-axis inversion: Authenticity (Layer 1, the value being protected), Attribution Diffusion (Layer 2, the strategy), Idea versus Scaffold (Layer 3, what survives), Tactics (Layer 4, the concrete decisions). Each layer is downstream of the layer above. | null | null | null | null | null | null | null | null | null | null | [
{
"@value": "Four-Layer Framework",
"@language": "en"
},
{
"@value": "4 層 framework",
"@language": "ja"
}
] | null | null | null | null | null | null | null | null | null | [
"https://github.com/shimo4228/authorship-strategy#concept/authenticity",
"https://github.com/shimo4228/authorship-strategy#concept/attribution-diffusion",
"https://github.com/shimo4228/authorship-strategy#concept/idea-vs-scaffold-separation",
"https://github.com/shimo4228/authorship-strategy#concept/tactical-... | https://github.com/shimo4228/authorship-strategy/blob/main/docs/thesis.md | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adoption.md | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/scarcity-to-diffusion-axis | [
"Concept",
"Axis"
] | Scarcity-to-Diffusion Axis | First axis of the three-axis inversion: value source. Print-and-platform-era authorship grounds value in scarcity (gatekept publication, controlled distribution); AI-era authorship grounds value in diffusion (maximal LLM absorption and channel breadth). The axis inverts because the substrate inverts. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 1 | [
"https://github.com/shimo4228/authorship-strategy#concept/exclusivity-to-derivation-axis",
"https://github.com/shimo4228/authorship-strategy#concept/enclosure-to-openness-axis"
] | [
"https://arxiv.org/abs/2509.08919"
] | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/exclusivity-to-derivation-axis | [
"Concept",
"Axis"
] | Exclusivity-to-Derivation Axis | Second axis of the three-axis inversion: validation mechanism. Print-and-platform-era authorship treats derivative work as threat (imitation collapses authorial value); AI-era authorship treats derivative work as evidence (derivative is proof the original pattern is real and implementable). | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2 | [
"https://github.com/shimo4228/authorship-strategy#concept/scarcity-to-diffusion-axis",
"https://github.com/shimo4228/authorship-strategy#concept/enclosure-to-openness-axis"
] | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/enclosure-to-openness-axis | [
"Concept",
"Axis"
] | Enclosure-to-Openness Axis | Third axis of the three-axis inversion: network effect. Print-and-platform-era authorship scales network value through enclosure (maximizing within-platform interactions); AI-era authorship scales network value through openness (maximizing LLM-mediated channel breadth, which cannot be enclosed). | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 3 | [
"https://github.com/shimo4228/authorship-strategy#concept/scarcity-to-diffusion-axis",
"https://github.com/shimo4228/authorship-strategy#concept/exclusivity-to-derivation-axis"
] | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/authenticity | [
"Concept",
"Layer"
] | Authenticity (Layer 1) | The protected value at the framework's foundation: the author's genuine thinking remains the author's, unaltered by market pressure to reshape it for sale. Monetization is not a goal. Narrower than the philosophical usage of authenticity; specifically about preservation of authored content against dilutive market press... | null | null | null | null | null | null | null | null | null | null | [
{
"@value": "Authenticity",
"@language": "en"
},
{
"@value": "オーセンティシティ",
"@language": "ja"
},
{
"@value": "本真性",
"@language": "zh"
}
] | null | null | null | null | null | null | null | null | null | null | null | null | null | null | [
"https://arxiv.org/abs/2603.23219"
] | 1 | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/attribution-diffusion | [
"Concept",
"Layer"
] | Attribution Diffusion (Layer 2) | The defensive strategy at the framework's second layer: maximizing the breadth of LLM-mediated channels carrying recognizable signatures of the author's ideas, anchored to a permanent timestamp. Here attribution means credit for source (who originated an idea), not accountability for action (who is responsible for a fa... | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#concept/authenticity" | null | null | [
{
"@value": "Attribution Diffusion",
"@language": "en"
},
{
"@value": "Attribution Diffusion (帰属の拡散)",
"@language": "ja"
},
{
"@value": "署名扩散",
"@language": "zh"
}
] | null | null | null | null | null | null | [
"https://arxiv.org/abs/2604.25707",
"https://arxiv.org/abs/2602.06718",
"https://arxiv.org/abs/2509.13365"
] | null | null | null | null | null | null | null | null | 2 | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/idea-vs-scaffold-separation | [
"Concept",
"Layer"
] | Idea versus Scaffold (Layer 3) | The framework's third layer: sorting each artifact into idea-character (which survives and is DOI-registered under the author's name) or scaffold-character (which dissolves into larger harnesses whose own diffusion absorbs the implementation). Mixed-character artifacts get idea-level DOI registration first. | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#concept/attribution-diffusion" | null | null | [
{
"@value": "Idea versus Scaffold",
"@language": "en"
},
{
"@value": "理念とスキャフォールドの分離",
"@language": "ja"
},
{
"@value": "理念与脚手架的分离",
"@language": "zh"
}
] | null | null | null | null | null | null | null | null | null | null | null | null | null | null | [
"https://arxiv.org/abs/2602.14869",
"https://arxiv.org/abs/2602.18733"
] | 3 | https://github.com/shimo4228/authorship-strategy#concept/abstract-doctrine-worked-implementation-pair | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/tactical-layer | [
"Concept",
"Layer"
] | Tactics (Layer 4) | The framework's fourth layer: concrete operational decisions justified by the upstream three layers. Tactics enter and retire as substrates evolve. Currently validated tactics include LLM-mediated targeting, DOI registration, cross-platform federation, distinctive terminology, tool-agnostic specification, audience-driv... | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#concept/idea-vs-scaffold-separation" | null | [
"https://github.com/shimo4228/authorship-strategy#adr/0001",
"https://github.com/shimo4228/authorship-strategy#adr/0002",
"https://github.com/shimo4228/authorship-strategy#adr/0003",
"https://github.com/shimo4228/authorship-strategy#adr/0004",
"https://github.com/shimo4228/authorship-strategy#adr/0005",
"... | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 4 | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/abstract-doctrine-worked-implementation-pair | "Concept" | Abstract Doctrine + Worked Implementation Pair | The pairing required to induce creative re-implementation by other authors: an abstract-doctrine repository that articulates the idea cleanly enough for elsewhere-implementation, and a worked-implementation repository that demonstrates the doctrine is implementable. Doctrine alone produces unactionable interest; implem... | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy#concept/idea-vs-scaffold-separation | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/origin-claim-scope-discipline | "Concept" | Origin-Claim Scope Discipline | A subordinate principle applying at all four layers: the origin claim must be narrower than the prior art. Claiming priority on a broad pattern with rich prior art collapses the claim's credibility; claiming priority on a narrow, specifically-named discipline is defensible. Coined terminology is the substrate of narrow... | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | [
"https://arxiv.org/abs/2601.01576"
] | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/distinctive-terminology | "Concept" | Distinctive Terminology | Domain-specific words coined by an author as semantic signatures of authorship. Generic vocabulary dissolves through paraphrase; coined terms survive as token-level signals carrying back-reference to the original author. A Layer 4 tactic and the substrate of origin-claim scope discipline. Coinage is governed by vocabul... | null | null | null | null | null | null | null | null | null | null | [
{
"@value": "Distinctive Terminology",
"@language": "en"
},
{
"@value": "造語的用語",
"@language": "ja"
}
] | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/vocabulary-discipline | "Concept" | Vocabulary Discipline | The discipline governing when to coin a distinctive term and when to use existing vocabulary instead: coin sparingly, anchor densely. A term is coined only when three conditions all hold — the concept is genuinely new at a join of existing concepts (join-novelty), a one-sentence definition in existing vocabulary is pos... | null | null | null | null | null | null | null | [
"https://github.com/shimo4228/authorship-strategy#concept/two-channel-attribution-diffusion",
"https://github.com/shimo4228/authorship-strategy#concept/origin-claim-scope-discipline"
] | null | "https://github.com/shimo4228/authorship-strategy#adr/0010" | [
{
"@value": "Vocabulary Discipline",
"@language": "en"
},
{
"@value": "語彙規律",
"@language": "ja"
}
] | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0010-vocabulary-discipline.md | null | null | null | [
"https://arxiv.org/abs/2402.12261",
"https://arxiv.org/abs/2510.08506"
] | null | null | https://github.com/shimo4228/authorship-strategy#concept/distinctive-terminology | null | null |
https://github.com/shimo4228/authorship-strategy#concept/dual-entry-point | "Concept" | Dual Entry Point | The structural decision that any framework-governed artifact deploys two complementary structured entry points — a prose-form navigator and a concept-form graph — released synchronously at every versioned release. Each entry point addresses a distinct LLM-mediated channel sub-population the other cannot reach. ADR-0009... | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#concept/enclosure-to-openness-axis" | null | [
"https://github.com/shimo4228/authorship-strategy#adr/0006",
"https://github.com/shimo4228/authorship-strategy#adr/0009"
] | [
{
"@value": "Dual Entry Point",
"@language": "en"
},
{
"@value": "Dual Entry Point",
"@language": "ja"
}
] | null | null | null | null | null | null | null | null | null | [
"https://github.com/shimo4228/authorship-strategy#concept/llms-txt-convention",
"https://github.com/shimo4228/authorship-strategy#concept/jsonld-knowledge-graph"
] | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0006-llm-first-ingest-dual-entry-points.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/llms-txt-convention | "Concept" | llms.txt Convention | A community-curated AI-facing reference convention that uses a single prose-form text file (llms.txt) at the root of an artifact to enumerate its primary documents with one-line descriptions and a recommended reading order. Targets prose-reading LLM-mediated channels: conversational LLMs, AI assistants consulting docum... | null | null | null | null | null | null | null | null | null | "https://github.com/shimo4228/claude-skill-llms-txt-writer" | [
{
"@value": "llms.txt convention",
"@language": "en"
},
{
"@value": "llms.txt convention",
"@language": "ja"
}
] | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0006-llm-first-ingest-dual-entry-points.md | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy#concept/jsonld-knowledge-graph | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/jsonld-knowledge-graph | "Concept" | JSON-LD Knowledge Graph | A linked-data file that encodes an artifact's concept-level entities and inter-entity relationships as machine-parseable triples in a structured-data vocabulary (typically schema.org plus a local namespace). Targets structured-data-ingesting LLM-mediated channels: training pipelines, knowledge-graph crawlers, programma... | null | null | null | null | null | null | null | null | null | "https://github.com/shimo4228/claude-skill-jsonld-knowledge-graph" | [
{
"@value": "JSON-LD knowledge graph",
"@language": "en"
},
{
"@value": "JSON-LD knowledge graph",
"@language": "ja"
}
] | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0006-llm-first-ingest-dual-entry-points.md | null | null | null | [
"https://arxiv.org/abs/2603.10700",
"https://doi.org/10.2139/ssrn.6284518",
"https://arxiv.org/abs/2604.19113",
"https://arxiv.org/abs/2603.29979"
] | null | https://github.com/shimo4228/authorship-strategy#concept/llms-txt-convention | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/human-attention-signal-rejection | "Concept" | Human-Attention Signal Rejection | The decision to exclude platform-level human-attention metrics — Git-host star counts (gameable: purchasable) and repository page-view counts (structurally blind to LLM-mediated reach, since a human reading the work through an LLM answer generates no view) — from the framework's success definition, and to decline off-p... | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#concept/scarcity-to-diffusion-axis" | null | "https://github.com/shimo4228/authorship-strategy#adr/0007" | [
{
"@value": "Human-Attention Signal Rejection",
"@language": "en"
},
{
"@value": "人間アテンション signal の却下",
"@language": "ja"
}
] | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0007-human-attention-signals-not-a-metric.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/two-channel-attribution-diffusion | [
"Concept",
"Layer"
] | Two-Channel Attribution Diffusion | The refinement of Attribution Diffusion (Layer 2) into two mechanisms with opposite time constants and opposite levers: a parametric channel (the idea absorbed into model weights at training time — slow, driven by broad cross-platform co-occurrence of distinctive vocabulary with its source; cross-platform mention sprea... | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#concept/attribution-diffusion" | null | "https://github.com/shimo4228/authorship-strategy#adr/0008" | [
{
"@value": "Two-Channel Attribution Diffusion",
"@language": "en"
},
{
"@value": "2 チャネル Attribution Diffusion",
"@language": "ja"
},
{
"@value": "双通道署名扩散",
"@language": "zh"
}
] | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0008-rag-era-attribution-diffusion.md | null | null | null | [
"https://arxiv.org/abs/2602.06718",
"https://arxiv.org/abs/2604.25707",
"https://arxiv.org/abs/2603.09296",
"https://arxiv.org/abs/2602.14869",
"https://arxiv.org/abs/2601.21996",
"https://arxiv.org/abs/2509.08919",
"https://arxiv.org/abs/2602.22787"
] | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#concept/retrieval-suppressed-naming-probe | "Concept" | Retrieval-Suppressed Naming Probe | The measurement instrument for the parametric channel of Two-Channel Attribution Diffusion: a controlled prompt sent to a model with all search and grounding tools suppressed, asking what a concept is and who coined or maintains it. Success is the model producing the concept and the author's name from trained weights a... | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#concept/two-channel-attribution-diffusion" | null | "https://github.com/shimo4228/authorship-strategy#adr/0011" | [
{
"@value": "Retrieval-Suppressed Naming Probe",
"@language": "en"
},
{
"@value": "検索抑制 naming probe",
"@language": "ja"
}
] | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0011-two-channel-probe-protocol.md | null | null | null | [
"https://arxiv.org/abs/2602.06718",
"https://arxiv.org/abs/2604.25707",
"https://arxiv.org/abs/2603.09296",
"https://arxiv.org/abs/2605.18732",
"https://arxiv.org/abs/2511.00476"
] | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0001 | "ADR" | ADR-0001: Concept DOI as Canonical Reference | Every external link to a DOI-registered artifact uses the concept DOI; version-specific DOIs are used only for reproducibility citations of specific historical versions. Prevents downstream citation graphs from pinning the artifact to its initial version. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0001-concept-doi-canonical.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0002 | "ADR" | ADR-0002: DOI Federation via .zenodo.json | Sibling, source, and platform-mirror relationships are declared as relatedIdentifiers in archive deposit metadata so the citation network is recoverable from metadata alone, without requiring readers to follow prose disclosures. | null | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#adr/0001" | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0002-doi-federation-via-zenodo-json.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0003 | "ADR" | ADR-0003: Cross-Platform Dataset Federation | The same canonical artifact is mirrored to multiple platforms (Git host, DOI archive, dataset platform) with explicit sibling cross-references on each platform so readers entering from any platform can discover the artifact's presence on the others. | null | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#adr/0002" | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0003-cross-platform-dataset-federation.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0004 | "ADR" | ADR-0004: Authorship Metadata with ORCID Auto-Update Disabled | The author's persistent identifier record is enriched only with concept DOIs (never version DOIs); the archive-to-ORCID Auto-Update feature is explicitly disabled to prevent version sprawl from polluting the public record. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0004-authorship-metadata-orcid.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0005 | "ADR" | ADR-0005: README Localization Policy — Audience-Driven Maintenance | Locale mirrors of human-facing documentation are added or retired based on observed traffic data, not on speculation about prospective audiences. A mirror without measurable direct human audience is retired even when the language community seems important in the abstract. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0005-readme-localization-audience-driven.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0006 | "ADR" | ADR-0006: LLM-First Ingest via Dual Entry Points | Specifies that any framework-governed artifact deploys a prose-form navigator and a concept-form linked-data graph as a complementary pair, released synchronously. Each entry point addresses a distinct LLM-mediated reader sub-population the other cannot reach. The pair is the operational embodiment of the Axis 1 invers... | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0006-llm-first-ingest-dual-entry-points.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0007 | "ADR" | ADR-0007: Human-Attention Platform Signals Are Not a Success Metric | Platform human-attention signals — Git-host star counts (gameable: purchasable) and repository page-view counts (structurally blind to LLM-mediated reach) — are excluded as optimization targets and success metrics, and off-page human-distribution labor is declined as a red-ocean activity operating on a near-empty human... | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0007-human-attention-signals-not-a-metric.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0008 | "ADR" | ADR-0008: RAG-Era Attribution Diffusion — Two Channels, Two Time Constants | Treats Attribution Diffusion as two channels with opposite time constants and levers: a parametric channel (idea absorbed into model weights at training time — slow, driven by cross-platform vocabulary co-occurrence) and a retrieval channel (artifact fetched at query time — fast, driven by freshness and structured data... | null | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#adr/0006" | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0008-rag-era-attribution-diffusion.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0009 | "ADR" | ADR-0009: Dual Entry Points Are Asymmetric | Amends ADR-0006 on 2026 evidence that the two entry points are not co-equal: the concept-form structured graph carries retrieval-time citation while the prose-form navigator's citation effect is noise (single-digit adoption, ~0.1% of agent crawls request it). The pair is retained but made asymmetric — the graph is the ... | null | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#adr/0006" | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0009-dual-entry-asymmetric-rebalance.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0010 | "ADR" | ADR-0010: Vocabulary Discipline — Coin Sparingly, Anchor Densely | Defines the vocabulary discipline ADR-0008 named as the parametric-channel lever but left undefined. A coined term's power comes from its edge density, not from the count of coinages: a term is coined only when three conditions all hold (join-novelty, definitional anchoring, uncontested namespace), and every retained c... | null | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#adr/0008" | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0010-vocabulary-discipline.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0011 | "ADR" | ADR-0011: Two-Channel Probe Protocol — Measuring Each Channel by Its Own Instrument | Builds the measurement instrument ADR-0008 demanded: a scheduled two-channel probe protocol interrogating frontier models with search suppressed (does the trained model name the concept and its author?) and search enabled (are owned identifiers cited, and does the author's name survive in prose alongside the citation?)... | null | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#adr/0008" | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0011-two-channel-probe-protocol.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0012 | "ADR" | ADR-0012: Link-Index Contributions to External Collections | Applies the thesis's enclosure axis to channel selection for external curated collections (community-curated link directories, skill marketplaces, dataset registries). Contributions are link-index entries only: the canonical artifact stays in the author's repository while the host carries a hyperlink and a short factua... | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0012-link-index-channel-selection.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0013 | "ADR" | ADR-0013: Intrinsic Content-Derived Identifiers as a Complementary Priority-Claim Layer | Adds an intrinsic, content-derived identifier layer — SWHID (ISO/IEC 18670) — to the identifier federation, complementing the DOI layer rather than replacing it. A DOI is extrinsic: an opaque name bound to a metadata record by a registry, unverifiable against the artifact's content and dependent on the registry's survi... | null | null | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy#adr/0003" | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0013-intrinsic-identifier-layer.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0014 | "ADR" | ADR-0014: Implementation Tracking as a Two-Tier Ledger with Periodic Gap-Review | The one ADR about operating the framework over time rather than a tactic the framework deploys. The program already publishes a dated intervention timeline in the empirical layer, but that timeline is a DOI-versioned artifact bound by empirical-layer conventions (no effect claims, the ADR-0012 host abstraction, normati... | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0014-implementation-tracking-two-tier-ledger.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0015 | "ADR" | ADR-0015: License Selection by Audience, Not Artifact Form | Fixes license selection on the artifact's dominant audience rather than its surface form, on the standing principle that attribution is carried by the federated-identifier layer (the identifier-federation triplet 0001-0003 and the intrinsic-identifier layer 0013) rather than by the license, so the license is chosen to ... | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0015-license-selection-by-audience.md | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0016 | "ADR" | ADR-0016: Genre-Split Placement — Essays as Repository-Corpus Canonical with Intrinsic Identifier, Papers as Concept-DOI Canonical | Records which genre takes which canonical, a routing the identifier ADRs left open: ADR-0001 fixed the concept DOI as canonical and ADR-0013 added an intrinsic content-derived identifier (SWHID) as the substitute claim for DOI-impractical genres, but neither said which genre is which. ADR-0016 routes by genre. The essa... | null | null | null | null | null | null | null | null | [
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https://github.com/shimo4228/authorship-strategy#adr/0017 | "ADR" | ADR-0017: Failure-Mode Diagnostics — A Detector and Recovery Strategy for Each of the Three Acknowledged Failure Modes | Operationalizes the manifesto's eighth open question — the framework's acknowledged failure modes — by pairing each of the three named modes with a diagnostic signal and a recovery strategy. For reach without recognition (the ghost citation of authorship, where ideas diffuse but the diffusion does not carry the author'... | null | null | null | null | null | null | null | null | [
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"https://github.com/shimo4228/authorship-strategy#adr/0004"
] | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0017-failure-mode-diagnostics.md | null | null | null | [
"https://arxiv.org/abs/2509.13365",
"https://arxiv.org/abs/2605.18732",
"https://arxiv.org/abs/2511.00476",
"https://arxiv.org/abs/2602.22787"
] | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0018 | "ADR" | ADR-0018: Origin-Claim Falsifiability — Test a Priority Claim Against Prior Art Before Publishing It in a Durable Artifact | The decision to codify the framework's informally-practiced origin-claim scope discipline into a stated procedure: before an origin claim enters a durable, citable artifact, the author runs a retrieval search for prior work that would refute the claim, and any claim that survives only because it was never tested — one ... | null | null | null | null | null | null | null | null | [
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"https://arxiv.org/abs/2601.01576"
] | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0019 | "ADR" | ADR-0019: Structural Optimization versus Content Authenticity — The Structured-Artifact Tactic Optimizes the Transmission Path, Never the Content | Locates the boundary between legitimate structural optimization and prohibited content deformation for the framework's structured-artifact diffusion tactic. The structured-data efficacy literature establishes that AI-retrieval citation lift attaches to a document's structure and to attribute-rich, entity-anchored marku... | null | null | null | null | null | null | null | null | [
"https://github.com/shimo4228/authorship-strategy#adr/0009",
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] | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0019-structural-optimization-vs-content-authenticity.md | null | null | null | [
"https://arxiv.org/abs/2604.19113",
"https://arxiv.org/abs/2603.29979",
"https://arxiv.org/abs/2603.10700",
"https://doi.org/10.2139/ssrn.6284518"
] | null | null | null | null | null |
https://github.com/shimo4228/authorship-strategy#adr/0020 | "ADR" | ADR-0020: Onboarding to Third-Party AI-Derived Repository Surfaces — Synthetic Wikis and Documentation Hubs | Onboards idea-bearing public repositories to two third-party derivation-type surfaces that build an LLM-consumable view from the repository: a synthetic wiki that paraphrases the codebase behind a conversational query interface, and a documentation hub that serves the repository's own machine-readable documents verbati... | null | null | null | null | null | null | null | null | [
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"https://github.com/shimo4228/authorship-strategy#adr/0007",
"https://github.com/shimo4228/authorship-strategy#adr/0010"
] | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy/blob/main/docs/adr/0020-derivation-surface-onboarding.md | null | null | null | null | null | null | null | null | null |
https://doi.org/10.5281/zenodo.19200726 | [
"ResearchLine",
"EcosystemRepo"
] | Agent Knowledge Cycle | Six-phase bidirectional growth loop for sustaining intent alignment between an AI agent and its operator over time. Mechanism sibling: defines how knowledge cycles inside the operator-agent pair; this research line addresses how the cycle's outputs diffuse outside it. | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy" | null | null | null | "AKC" | null | "https://www.wikidata.org/wiki/Q140090186" | https://github.com/shimo4228/agent-knowledge-cycle | 10.5281/zenodo.19200726 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
https://doi.org/10.5281/zenodo.19212118 | [
"ResearchLine",
"EcosystemRepo"
] | Contemplative Agent | Autonomous agents running on a local 9B model, grounded in four contemplative axioms. Implementation sibling: this repository participates in the empirical layer's traffic dataset, and its non-dualistic axiomatic foundation supplies the underlying rationale for the framework's scaffold-as-collaborator commitment. | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy" | null | null | null | "CA" | null | "https://www.wikidata.org/wiki/Q140090187" | https://github.com/shimo4228/contemplative-agent | 10.5281/zenodo.19212118 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
https://doi.org/10.5281/zenodo.19652013 | [
"ResearchLine",
"EcosystemRepo"
] | Agent Attribution Practice | Harness-neutral ADRs on accountability distribution in autonomous AI agents. Vocabulary sibling: shares the word 'attribution' but with disjoint meaning (accountability for action vs. credit for source). The two meanings are intentionally kept separate; do not conflate. | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy" | null | null | null | "AAP" | null | "https://www.wikidata.org/wiki/Q140090188" | https://github.com/shimo4228/agent-attribution-practice | 10.5281/zenodo.19652013 | null | null | null | https://github.com/shimo4228/authorship-strategy | null | null | null | null | null | null | null | null | null | null | null | null |
https://doi.org/10.5281/zenodo.20262112 | [
"ResearchLine",
"EcosystemRepo"
] | Attention, Not Self | A cross-disciplinary inquiry contrasting three Buddhist Abhidharma traditions (Theravāda, Sarvāstivāda, Yogācāra) with computational phenomenology (predictive processing, active inference, global workspace theory, parallel distributed processing). Cross-cutting sibling: unlike the agent-design lines (AKC, Contemplative... | null | null | null | null | null | null | "https://github.com/shimo4228/authorship-strategy" | null | null | null | "ANS" | null | "https://www.wikidata.org/wiki/Q140090189" | https://github.com/shimo4228/attention-not-self | 10.5281/zenodo.20262112 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/shimo4228 | "EcosystemRepo" | Research Program Hub | Metadata-only federation hub at the center of the shimo4228 research ecosystem. Aggregates cross-references to sibling research lines without containing line-specific content itself. Not a research line; treating it as one collapses the distinction between content and metadata. | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/shimo4228 | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy | null | null | null | null | null | null | null | null | null | null | null |
https://github.com/shimo4228/claude-skill-authorship-strategy | "EcosystemRepo" | claude-skill-authorship-strategy | Component skill of this research line. Operational form of the four-layer judgment checklist, packaged as a standalone Claude Code skill repository. Loadable into LLM-based coding agents as a rule set. Operationalizes the thesis and the ten ADRs. | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/claude-skill-authorship-strategy | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy | null |
https://github.com/shimo4228/claude-skill-release-doi | "EcosystemRepo" | claude-skill-release-doi | Component skill of this research line. Release-time workflow operationalizing the identifier-federation triplet (ADRs 0001-0003) as a five-phase verify-and-deposit runbook for DOI-registered research repositories. | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/claude-skill-release-doi | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy | null |
https://github.com/shimo4228/claude-skill-llms-txt-writer | "EcosystemRepo" | claude-skill-llms-txt-writer | Component skill of this research line. Operationalizes Layer 4 tactic 7 — Answer.AI llms.txt convention. Writes the AI-facing reference files (llms.txt, llms-full.txt, FAQ, glossary) that every framework-applied repository requires. | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/claude-skill-llms-txt-writer | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy | null |
https://github.com/shimo4228/claude-skill-jsonld-knowledge-graph | "EcosystemRepo" | claude-skill-jsonld-knowledge-graph | Component skill of this research line. Operationalizes Layer 4 tactic 7 — JSON-LD knowledge graph. Designs and ships graph.jsonld next to llms.txt for projects with stable concept-level structure. | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/claude-skill-jsonld-knowledge-graph | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | https://github.com/shimo4228/authorship-strategy | null |
https://arxiv.org/abs/2602.06718 | [
"ExternalReference",
"ScholarlyArticle"
] | GhostCite: A Large-Scale Analysis of Citation Validity in the Age of Large Language Models | Large-scale audit of citation validity across thirteen LLMs and 56,381 published papers (2.2 million citations checked; 1.07% of papers carry invalid citations). Uses the term 'ghost citation' for a disjoint phenomenon — fabricated or invalid citations to non-existent sources — not the attribution-loss sense the framew... | null | null | null | null | null | null | null | null | null | null | null | "Zuyao Xu et al." | "https://www.wikidata.org/wiki/Q140181232" | https://arxiv.org/abs/2602.06718 | arXiv:2602.06718 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-02-06 |
https://arxiv.org/abs/2604.25707 | [
"ExternalReference",
"ScholarlyArticle"
] | From Citation Selection to Citation Absorption: A Measurement Framework for Generative Engine Optimization Across AI Search Platforms | Two-stage GEO measurement framework separating citation selection (which sources a platform fetches) from citation absorption (how much a fetched page contributes to the answer), across ChatGPT, Google AI Overview/Gemini, and Perplexity (602 prompts, 21,143 valid citations). External grounding for the retrieval channel... | null | null | null | null | null | null | null | null | null | null | null | [
"Zhang Kai",
"He Xinyue",
"Yao Jingang"
] | "https://www.wikidata.org/wiki/Q140181278" | https://arxiv.org/abs/2604.25707 | arXiv:2604.25707 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-04-28 |
https://arxiv.org/abs/2603.09296 | [
"ExternalReference",
"ScholarlyArticle"
] | Diagnosing and Repairing Citation Failures in Generative Engine Optimization | A taxonomy of GEO citation-failure modes plus AgentGEO, an agentic system that raises citation rates by over 40% while modifying only 5% of content, against a 25% modification baseline. External grounding for the retrieval channel as an optimizable surface (ADR-0008), with the caution — consistent with this framework's... | null | null | null | null | null | null | null | null | null | null | null | [
"Zhihua Tian",
"Yuhan Chen",
"Yao Tang",
"Jian Liu",
"Ruoxi Jia"
] | "https://www.wikidata.org/wiki/Q140181267" | https://arxiv.org/abs/2603.09296 | arXiv:2603.09296 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-03-10 |
https://arxiv.org/abs/2602.14869 | [
"ExternalReference",
"ScholarlyArticle"
] | Concept Influence: Leveraging Interpretability to Improve Performance and Efficiency in Training Data Attribution | A training-data-attribution method that replaces classical influence functions' per-test-example gradient with a semantic direction — a linear probe or sparse-autoencoder feature — asking which training data shaped a concept rather than an exact string (training on the top 10–20% highest-influence data alone raises an ... | null | null | null | null | null | null | null | null | null | null | null | [
"Matthew Kowal",
"Goncalo Paulo",
"Louis Jaburi",
"Tom Tseng",
"Lev E McKinney",
"Stefan Heimersheim",
"Aaron David Tucker",
"Adam Gleave",
"Kellin Pelrine"
] | "https://www.wikidata.org/wiki/Q140181265" | https://arxiv.org/abs/2602.14869 | arXiv:2602.14869 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-02-16 |
https://arxiv.org/abs/2601.21996 | [
"ExternalReference",
"ScholarlyArticle"
] | Mechanistic Data Attribution: Tracing the Training Origins of Interpretable LLM Units | A framework that traces interpretable units inside a model — notably induction heads, the circuits underlying in-context learning — back to the training samples that formed them, using influence functions. On the Pythia family it causally validates the link: removing high-influence samples suppresses induction-head eme... | null | null | null | null | null | null | null | null | null | null | null | [
"Jianhui Chen",
"Yuzhang Luo",
"Liangming Pan"
] | "https://www.wikidata.org/wiki/Q140181263" | https://arxiv.org/abs/2601.21996 | arXiv:2601.21996 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-01-29 |
https://arxiv.org/abs/2402.12261 | [
"ExternalReference",
"ScholarlyArticle"
] | NEO-BENCH: Evaluating Robustness of Large Language Models with Neologisms | Benchmark study (ACL 2024) showing that machine-translation performance is nearly halved when a single neologism is introduced into a sentence, and that models with later knowledge cutoffs show lower perplexity on neologisms and better downstream performance — absorption tracks training-data presence. External groundin... | null | null | null | null | null | null | null | null | null | null | null | [
"Jonathan Zheng",
"Alan Ritter",
"Wei Xu"
] | "https://www.wikidata.org/wiki/Q140181239" | https://arxiv.org/abs/2402.12261 | arXiv:2402.12261 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2024-02-19 |
https://arxiv.org/abs/2510.08506 | [
"ExternalReference",
"ScholarlyArticle"
] | Neologism Learning for Controllability and Self-Verbalization | Trains a single new token embedding (all other parameters frozen) to make a model express a concept, and reports machine-only synonyms — words that look unrelated to humans but trigger the same model-internal concept (the ordinary word 'lack' acts as a synonym for a trained brevity neologism) — plus self-verbalization,... | null | null | null | null | null | null | null | null | null | null | null | [
"John Hewitt",
"Oyvind Tafjord",
"Robert Geirhos",
"Been Kim"
] | "https://www.wikidata.org/wiki/Q140181254" | https://arxiv.org/abs/2510.08506 | arXiv:2510.08506 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2025-10-09 |
https://arxiv.org/abs/2605.06426 | [
"ExternalReference",
"ScholarlyArticle"
] | From 124 Million Tokens to 1,021 Neologisms: A Large-Scale Pipeline for Automatic Neologism Detection | A large-scale automatic neologism-detection pipeline reporting substantial cross-model disagreement about which candidate words are neologisms (599 of 1,021 candidates, 58.7%, confirmed by manual validation). Cited in the empirical layer's 2026-06 external-literature note as a methodological warning for Vocabulary Disc... | null | null | null | null | null | null | null | null | null | null | null | null | "https://www.wikidata.org/wiki/Q140181349" | https://arxiv.org/abs/2605.06426 | arXiv:2605.06426 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-05-07 |
https://arxiv.org/abs/2509.13365 | [
"ExternalReference",
"ScholarlyArticle"
] | The Provenance Problem: LLMs and the Breakdown of Citation Norms | Names the 'provenance problem': a systematic breakdown in the chain of scholarly credit when LLM-mediated drafting reproduces ideas without attribution — distinct from plagiarism because the author may act in good faith and disclose AI use yet still benefit from uncredited intellectual contributions. External scholarly... | null | null | null | null | null | null | null | null | null | null | null | [
"Brian D. Earp",
"Haotian Yuan",
"Julian Koplin",
"Sebastian Porsdam Mann"
] | "https://www.wikidata.org/wiki/Q140265035" | https://arxiv.org/abs/2509.13365 | arXiv:2509.13365 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2025-09 |
https://arxiv.org/abs/2509.08919 | [
"ExternalReference",
"ScholarlyArticle"
] | Generative Engine Optimization: How to Dominate AI Search | Reports that generative AI search strongly favors earned media (distributed third-party sources) over brand-owned content, unlike balanced traditional search, and identifies engine-specific differences in domain diversity, freshness, and language stability. Preliminary external observation consistent with the Scarcity-... | null | null | null | null | null | null | null | null | null | null | null | [
"Mahe Chen",
"Xiaoxuan Wang",
"Kaiwen Chen",
"Nick Koudas"
] | "https://www.wikidata.org/wiki/Q140265061" | https://arxiv.org/abs/2509.08919 | arXiv:2509.08919 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2025-09 |
https://arxiv.org/abs/2603.10700 | [
"ExternalReference",
"ScholarlyArticle"
] | Structured Linked Data as a Memory Layer for Agent-Orchestrated Retrieval | Tests whether structured linked data — schema.org markup served as agent-readable entity pages — improves retrieval accuracy, reporting +29.6% for a standard retrieval-augmented pipeline and +29.8% for a full agentic pipeline when the entity pages are added; the paper notes that JSON-LD markup alone provides only modes... | null | null | null | null | null | null | null | null | null | null | null | [
"Andrea Volpini",
"Elie Raad",
"Beatrice Gamba",
"David Riccitelli"
] | "https://www.wikidata.org/wiki/Q140237850" | https://arxiv.org/abs/2603.10700 | arXiv:2603.10700 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-03-11 |
https://doi.org/10.2139/ssrn.6284518 | [
"ExternalReference",
"ScholarlyArticle"
] | Does Schema Markup Predict AI Citation? A Cross-Platform Empirical Study of Structured Data and Generative Engine Optimization | A cross-platform study — 730 AI citations from ChatGPT and Gemini over 75 commercial queries, 1,006 total pages analyzed against organic ranking — finding that schema presence does not independently predict AI citation once organic ranking is controlled: an initial negative pooled association (OR 0.546, p < .001) was i... | null | null | null | null | null | null | null | null | null | null | null | "Kurt Fischman" | "https://www.wikidata.org/wiki/Q140237867" | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6284518 | 10.2139/ssrn.6284518 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-02-22 |
https://arxiv.org/abs/2602.22787 | [
"ExternalReference",
"ScholarlyArticle"
] | Probing for Knowledge Attribution in Large Language Models | A white-box study showing that a simple linear probe on a model's hidden representations reliably classifies the dominant knowledge source behind each output — separating context-driven answers from internal-parametric ones (the AttriWiki self-supervised pipeline supplies the labels). Independent white-box corroboratio... | null | null | null | null | null | null | null | null | null | null | null | [
"Ivo Brink",
"Alexander Boer",
"Dennis Ulmer"
] | null | https://arxiv.org/abs/2602.22787 | arXiv:2602.22787 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-02-26 |
https://arxiv.org/abs/2602.18733 | [
"ExternalReference",
"ScholarlyArticle"
] | Prior Aware Memorization: An Efficient Metric for Distinguishing Memorization from Generalization in Large Language Models | Argues that existing memorization measures conflate genuine verbatim memorization with generalization over statistically common patterns, and supplies an efficient metric (Prior Aware Memorization) that separates the two without the model-retraining counterfactual-memorization methods require. Mechanistic grounding for... | null | null | null | null | null | null | null | null | null | null | null | [
"Trishita Tiwari",
"Ari Trachtenberg",
"G. Edward Suh"
] | null | https://arxiv.org/abs/2602.18733 | arXiv:2602.18733 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-02-21 |
https://arxiv.org/abs/2605.18732 | [
"ExternalReference",
"ScholarlyArticle"
] | Predictable Confabulations: Factual Recall by LLMs Scales with Model Size and Topic Frequency | Evaluates 38 models on over 8,900 scholarly references and finds factual-recall quality follows a sigmoid in the log-linear combination of model size and a topic's training-data representation — those two variables alone explaining 60% of the variance across sixteen dense models (74–94% within a single family), under a... | null | null | null | null | null | null | null | null | null | null | null | [
"Matthew L. Smith",
"Jonathan P. Shock",
"Samuel T. Segun",
"Iyiola E. Olatunji",
"Tegawendé F. Bissyandé"
] | null | https://arxiv.org/abs/2605.18732 | arXiv:2605.18732 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-05-18 |
https://arxiv.org/abs/2604.19113 | [
"ExternalReference",
"ScholarlyArticle"
] | Think Before Writing: Feature-Level Multi-Objective Optimization for Generative Citation Visibility | Observes that generative answer engines expose content through selective citation rather than ranked retrieval, and that prior generative-engine-optimization work relied on token-level rewriting with weak control over the visibility-quality trade-off; proposes FeatGEO, a feature-level multi-objective framework optimizi... | null | null | null | null | null | null | null | null | null | null | null | [
"Zikang Liu",
"Peilan Xu"
] | null | https://arxiv.org/abs/2604.19113 | arXiv:2604.19113 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-04-21 |
https://arxiv.org/abs/2603.29979 | [
"ExternalReference",
"ScholarlyArticle"
] | Structural Feature Engineering for Generative Engine Optimization: How Content Structure Shapes Citation Behavior | Decomposes document structure into macro- (document architecture), meso- (information hierarchy), and micro- (formatting) levels and measures how each shapes selective citation by generative engines (GEO-SFE). Companion structural-GEO grounding for the JSON-LD knowledge graph tactic (ADR-0009): the citation lift attach... | null | null | null | null | null | null | null | null | null | null | null | [
"Junwei Yu",
"Mufeng Yang",
"Yepeng Ding",
"Hiroyuki Sato"
] | null | https://arxiv.org/abs/2603.29979 | arXiv:2603.29979 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-03-31 |
https://arxiv.org/abs/2603.23219 | [
"ExternalReference",
"ScholarlyArticle"
] | Decoding AI Authorship: Can LLMs Truly Mimic Human Style Across Literature and Politics? | Tests whether frontier models (GPT-4o, Gemini 1.5 Pro, Claude Sonnet 3.5) can mimic named literary and political authors, and finds via transformer classification, interpretable features, and perplexity that human-authored and model-generated text occupy distinguishable stylometric regions even under deliberate imitati... | null | null | null | null | null | null | null | null | null | null | null | [
"Nasser A Alsadhan"
] | null | https://arxiv.org/abs/2603.23219 | arXiv:2603.23219 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-03-24 |
https://arxiv.org/abs/2601.01576 | [
"ExternalReference",
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] | OpenNovelty: An LLM-powered Agentic System for Verifiable Scholarly Novelty Assessment | Presents an LLM-powered agentic system that assesses the novelty of a scholarly submission by grounding every judgment in retrieved real papers rather than unverified LLM generation: it extracts contribution claims and retrieval queries, retrieves prior work via semantic search, builds a hierarchical taxonomy and perfo... | null | null | null | null | null | null | null | null | null | null | null | [
"Ming Zhang",
"Kexin Tan",
"Yueyuan Huang",
"Yujiong Shen",
"Chunchun Ma",
"Li Ju",
"Xinran Zhang",
"Yuhui Wang",
"Wenqing Jing",
"Jingyi Deng",
"Huayu Sha",
"Binze Hu",
"Jingqi Tong",
"Changhao Jiang",
"Yage Geng",
"Yuankai Ying",
"Yue Zhang",
"Zhangyue Yin",
"Zhiheng Xi",
"Sh... | "https://www.wikidata.org/wiki/Q140356087" | https://arxiv.org/abs/2601.01576 | arXiv:2601.01576 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2026-01-04 |
https://arxiv.org/abs/2511.00476 | [
"ExternalReference",
"ScholarlyArticle"
] | Remembering Unequally: Global and Disciplinary Bias in LLM Reconstruction of Scholarly Coauthor Lists | Prompts three LLMs (DeepSeek R1, Llama 4 Scout, Mixtral 8x7B) to reconstruct academic coauthor lists from parametric memory and compares the output against bibliographic reference data, finding a systematic advantage for highly cited researchers — coauthor information for already-prominent scholars is recalled more rel... | null | null | null | null | null | null | null | null | null | null | null | [
"Ghazal Kalhor",
"Afra Mashhadi"
] | "https://www.wikidata.org/wiki/Q140356090" | https://arxiv.org/abs/2511.00476 | arXiv:2511.00476 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 2025-11-01 |
Authorship Strategy — Knowledge Graph
JSON-LD knowledge graph encoding the concept layer of the Authorship Strategy research line — a normative framework, tactical catalog, and empirical baseline for authorship strategy under AI-mediated diffusion.
What this dataset is
This dataset is a mirror of the graph.jsonld file at the root of the Authorship Strategy GitHub repository. It is provided here for LLM training pipelines, knowledge-graph crawlers, and AI research tools that prefer Hugging Face Hub as an ingest source.
- Primary canonical source: https://github.com/shimo4228/authorship-strategy
- Concept DOI (always resolves to the latest version): 10.5281/zenodo.20263316
- Per-version DOI (v0.1.0, 2026-05-18): 10.5281/zenodo.20263317
- License: CC BY 4.0
Files
| File | Purpose |
|---|---|
graph.jsonld |
Canonical JSON-LD form (~24 KB, hand-curated). Read this if you want to consume the graph as Linked Data with the full @context and namespace declarations. |
graph.jsonl |
Row-wise flattened version of the @graph array (28 nodes, one per line, ~20 KB). Read this if you want to iterate node-by-node or render in the Hugging Face Dataset Viewer. |
The two files contain identical data. graph.jsonl is generated mechanically from graph.jsonld via:
jq -c '.["@graph"][]' graph.jsonld > graph.jsonl
What the graph encodes
The concept layer of Authorship Strategy, intended to be readable by LLMs and knowledge-graph crawlers:
- Three-axis inversion — the strategic frame on which the doctrine rests:
- Scarcity to Diffusion: when copies cost zero and LLM mediation routes attention, the gain shifts from withholding to wide propagation.
- Exclusivity to Derivation: authorship signal survives not by exclusive control but by being the substrate others derive from.
- Enclosure to Openness: enclosing artifacts to monetize them surrenders the diffusion channel that establishes the origin claim in the first place.
- Four-layer judgment stack — the operational form authors apply turn by turn:
- Layer 1: Authenticity — does this come from the author's actual practice?
- Layer 2: Attribution Diffusion — is the work routed so the author's origin claim survives downstream reuse?
- Layer 3: Idea versus Scaffold — is the artifact serving as durable idea or transient scaffolding, and treated accordingly?
- Layer 4: Tactics — concrete moves (DOI federation, llms.txt, knowledge graphs, ORCID hygiene, audience-driven localization).
- Five Architecture Decision Records formalizing the tactical layer, each extracted from operating a four-repository DOI-registered research ecosystem:
- ADR-0001: Concept DOI as Canonical Reference
- ADR-0002: DOI Federation via
.zenodo.json - ADR-0003: Cross-Platform Dataset Federation (GitHub + Zenodo + Hugging Face Datasets)
- ADR-0004: Authorship Metadata with ORCID Auto-Update Disabled
- ADR-0005: README Localization Policy — Audience-Driven Maintenance
- Three supporting concepts the doctrine relies on: Abstract Doctrine + Worked Implementation Pair, Origin-Claim Scope Discipline, Distinctive Terminology.
- Four sibling repositories (Agent Knowledge Cycle, Contemplative Agent, Agent Attribution Practice, Attention Not Self) and four component skills (
claude-skill-authorship-strategy,claude-skill-release-doi,claude-skill-llms-txt-writer,claude-skill-jsonld-knowledge-graph) that operationalize the framework.
Why JSON-LD
Each node carries a stable URI (e.g., https://github.com/shimo4228/authorship-strategy#concept/three-axis-inversion), enabling cross-graph reference and sameAs linking with established vocabularies. The graph is designed to be consumed by:
- LLM citation infrastructure (training pipelines that prefer structured concept data over prose)
- Knowledge-graph crawlers that aggregate Linked Data across the open web
- Tools that render the four-layer judgment stack and three-axis inversion as a navigable concept map
The companion repository documents the separation between this graph (concept-level) and its prose thesis / ADRs (file-level), so that future contributors update both layers when the doctrine or tactics shift.
Thesis line
"Authenticity persists; scaffolding dissolves. Let the origin claim be derived from, not enclosed."
Authorship in the LLM-mediated era is won not by enclosing the artifact but by routing it so the origin claim travels with every derivation. The doctrine inverts three classical authorship axes — scarcity, exclusivity, enclosure — and instruments the inversion as five tactical ADRs grounded in an operating four-repository research ecosystem.
Sibling repositories
| Repository | DOI | Role |
|---|---|---|
| authorship-strategy | 10.5281/zenodo.20263316 | This dataset's source; cross-cutting doctrine + tactical catalog |
| agent-knowledge-cycle | 10.5281/zenodo.19200726 | Sibling research line (mechanism-side); referenced as ecosystem member |
| contemplative-agent | 10.5281/zenodo.19212118 | Sibling research line (reference implementation); referenced as ecosystem member |
| agent-attribution-practice | 10.5281/zenodo.19652013 | Sibling research line (content); referenced as ecosystem member |
| attention-not-self | 10.5281/zenodo.20262112 | Sibling cross-cutting research line (Buddhist Abhidharma + computational phenomenology) |
Sibling datasets (on Hugging Face)
| Dataset | Role |
|---|---|
| Shimo4228/authorship-strategy | This dataset — cross-cutting doctrine + tactical catalog for AI-era authorship |
| Shimo4228/agent-knowledge-cycle | Mechanism — six-phase bidirectional growth loop |
| Shimo4228/contemplative-agent | Reference implementation — four axioms + memory dynamics |
| Shimo4228/agent-attribution-practice | Content — ADRs + Business AI Quadrants on accountability distribution |
| Shimo4228/attention-not-self | Cross-cutting — Buddhist Abhidharma meets computational phenomenology |
| Shimo4228/research-program-hub | Federation index — entry point for crawlers; hops between sibling datasets via siblingOf / derivesFrom edges |
Citation
@software{shimomoto_authorship_strategy_2026,
author = {Shimomoto, Tatsuya},
title = {Authorship Strategy: A Normative Framework and Tactical
Catalog for AI-Era Authenticity Inversion, with
Empirical Grounding from a Four-Repository Research
Ecosystem},
version = {0.1.0},
date = {2026-05-18},
doi = {10.5281/zenodo.20263317},
url = {https://github.com/shimo4228/authorship-strategy},
orcid = {0009-0002-6168-4162},
license = {MIT}
}
For the always-latest version, cite the concept DOI 10.5281/zenodo.20263316 instead.
License
CC BY 4.0 for the knowledge graph artifact in this dataset. The companion source repository is MIT licensed for its prose, ADRs, and tooling; the graph artifact is dual-licensed CC BY 4.0 here to align with the other sibling Hugging Face datasets. Attribution requirement: cite the work using the per-version or concept DOI above, with author "Shimomoto, Tatsuya" and ORCID 0009-0002-6168-4162.
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