feat: v2.3 — CTS enrichment pass, coverage 42.4% → 46.4% unique / 71.8% → 75.4% records

- 997 unique compounds resolved via PubChem name variants
- 2,741 records improved (hyphen→space normalization key)
- CTS API tested: 0% yield for ethnobotanical names
- Documented CTS methodology in METHODOLOGY.md
- Updated pricing: Early Bird removed, standard €699/€1,349/€1,699
- Enterprise: Stripe checkout → mailto lead capture
- JSON: 25.6 MB | Parquet: 1,211 KB
- SHA-256 JSON: 956cd7b08d279792...
- SHA-256 Parquet: 4b7351048db025cb...

METHODOLOGY.md

@@ -1,6 +1,6 @@
-# Methodology — Ethno-API Phytochemical Dataset v2.2
+# Methodology — Ethno-API Phytochemical Dataset v2.3
 
-> **Schema v2.2 · 76,907 records · 24,746 compounds · 2,313 species · 10 fields**
+> **Schema v2.3 · 76,907 records · 24,746 compounds · 2,313 species · 10 fields**
 
 ---
 
@@ -17,7 +17,7 @@
 
 ---
 
-## Schema v2.2
+## Schema v2.3
 
 | Field | Type | Null Count | Description |
 |---|---|---|---|
@@ -29,8 +29,8 @@
 | `clinical_trials_count_2026` | Int64 | 0 | ClinicalTrials.gov study count mentioning compound |
 | `chembl_bioactivity_count` | Int64 | 0 | ChEMBL bioactivity assay count |
 | `patent_count_since_2020` | Int64 | 0 | US patent count (USPTO PatentsView, since 2020-01-01) |
-| `pubchem_cid` | Int64 | 14,262 | PubChem Compound ID (CID) — 42.4% of unique compounds resolved |
-| `canonical_smiles` | string | 14,262 | Canonical SMILES string (PubChem) — 42.4% of unique compounds resolved |
+| `pubchem_cid` | Int64 | 13,265 | PubChem Compound ID (CID) — 46.4% of unique compounds resolved |
+| `canonical_smiles` | string | 13,265 | Canonical SMILES string (PubChem) — 46.4% of unique compounds resolved |
 
 **Enrichment coverage:**
 
@@ -96,13 +96,29 @@
 - **Endpoint:** `https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/{name}/JSON`
 - **Query logic:** Name-to-CID resolution, returns `CID` + `CanonicalSMILES`
 - **Queries:** 24,746 unique compound names
-- **Resolved:** 10,484 compounds (42.4% of unique chemicals)
-- **Unresolved:** 14,262 compounds (null in schema)
+- **Resolved:** 11,481 compounds (46.4% of unique chemicals)
+- **Unresolved:** 13,265 compounds (null in schema)
 - **Rate limit:** 0.35s between requests, checkpoint-resumable
 - **Runtime:** 3.2 hours (24,746 queries)
 - **Output fields:** `canonical_smiles`, `pubchem_cid`
 
-> **Why 57.6% are null:** Phytochemical trivial names (e.g. "TANNIN", "RESIN"), plant mixture descriptions (e.g. "ESSENTIAL OIL"), and non-specific ethnobotanical terms are not indexed in PubChem's compound database by name. These are inherent limitations of the source data, not pipeline failures.
+> **Why 53.6% are null:** Phytochemical trivial names (e.g. "TANNIN", "RESIN"), plant mixture descriptions (e.g. "ESSENTIAL OIL"), and non-specific ethnobotanical terms are not indexed in PubChem's compound database by name. These are inherent limitations of the source data, not pipeline failures.
+
+### 7. CTS Synonym Enrichment (v2.3)
+
+- **Goal:** Reduce the null-rate for `pubchem_cid` and `canonical_smiles` through systematic name variant resolution
+- **Candidates:** 14,197 compounds without PubChem CID (after excluding truncated names and length < 3)
+- **CTS API test:** UC Davis Chemical Translation Service tested first — **0% yield** for all ethnobotanical trivial names → CTS not suitable for this nomenclature
+- **PubChem PUG-REST name variants:** 4 variants per compound:
+  1. Original (e.g. `GALACTURONIC-ACID`)
+  2. Hyphens → spaces (`galacturonic acid`)
+  3. Lowercase (`galacturonic-acid`)
+  4. Lowercase + spaces (`galacturonic acid`)
+- **Checkpoint system:** Resume-safe, persisted every 100 API calls
+- **Runtime:** ~3.5 hours at ~4.5 req/s
+- **Result:** 997 unique compounds newly resolved (7.0% of candidates), 2,741 records improved
+- **Coverage improvement:** 42.4% → **46.4%** unique compounds (10,484 → 11,481), 71.8% → **75.4%** records (55,217 → 57,958)
+- **Remaining nulls:** 13,265 unique compounds (53.6%) are genuinely unresolvable — collective nouns (tannins, phytosterols, mucilage), historical herbal medicine names without PubChem entries, unresolved USDA Dr. Duke nomenclature from the 1980s/90s
 
 ---
 
@@ -171,6 +187,7 @@ All enrichment scripts are available in the repository:
 | v2.0 | 2026-03 | 8 (+clinical_trials_count_2026, chembl_bioactivity_count, patent_count_since_2020) | 76,907 | 4-source enrichment, DQA audit (noise compounds + duplicates removed: 104,388 → 76,907), checkpoint system. Superseded by v2.1/v2.2. |
 | v2.1 | 2026-03 | 10 (+pubchem_cid, canonical_smiles) | 76,907 | PubChem CID + SMILES enrichment (10,484 chemicals resolved, 71.8% record coverage — corrected to 42.4% in v2.2) |
 | v2.2 | 2026-03 | 10 (same schema) | 76,907 | Stereo-prefix normalization for CT matching (+2 compounds), corrected SMILES coverage reporting (42.4% of unique chemicals), local CT XML matching replaces API |
+| **v2.3** | **2026-03** | **10 (same schema)** | **76,907** | **CTS synonym enrichment: 997 compounds resolved via PubChem name variants (hyphen→space normalization), PubChem CID coverage 42.4%→46.4% unique / 71.8%→75.4% records** |
 
 ---
 
@@ -186,4 +203,7 @@ All enrichment scripts are available in the repository:
 | `ethno_dataset_2026_v2.2.json` | 25.4 MB | `7cb5719f9763f84f1cb8176b462d51fd9df5750e7cfa78e497263b7631ebba13` |
 | `ethno_dataset_2026_v2.2.parquet` | 1.2 MB | `118d28bf08b784868b60fc1445a0fdd6817d5d8a492015c51d975cf8e8e5a132` |
 
-Export timestamp: `2026-03-22T14:29:03Z` (v2.2 final)
+| `ethno_dataset_2026_v2.3.json` | 25.6 MB | `956cd7b08d279792e132629ce608ab72eb9249b09ac84ed9c60bd108acb5057e` |
+| `ethno_dataset_2026_v2.3.parquet` | 1,211 KB | `4b7351048db025cbf575b4538e66afd70729c327b8a0b48ead87d5546a39762e` |
+
+Export timestamp: `2026-03-25T12:00:00Z` (v2.3 final)

README.md

@@ -7,7 +7,7 @@ language:
 - en
 license: cc-by-4.0
 multilinguality: monolingual
-pretty_name: "USDA Phytochemical & Ethnobotanical Database — Enriched v2.2"
+pretty_name: "USDA Phytochemical & Ethnobotanical Database — Enriched v2.3"
 size_categories:
 - 100K<n<1M
 source_datasets:
@@ -61,7 +61,7 @@ dataset_info:
   config_name: default
 ---
 
-> **Full dataset available:** Single €699 · Team €1,349 · Enterprise €1,699. [→ ethno-api.com](https://ethno-api.com)
+> **Production-grade phytochemical data.** Single €699 · Team €1,349 · Enterprise €1,699. [→ ethno-api.com](https://ethno-api.com)
 
 <div align="center">
 
@@ -70,12 +70,12 @@ dataset_info:
 If you use this dataset in your research, please cite:
 
 ```
-Wirth, A. (2026). USDA Phytochemical Database — Enriched v2.2 (Sample). Zenodo. https://doi.org/10.5281/zenodo.15083493
+Wirth, A. (2026). USDA Phytochemical Database — Enriched v2.3 (Sample). Zenodo. https://doi.org/10.5281/zenodo.19053087
 ```
 
 ---
 
-# USDA Phytochemical & Ethnobotanical Database — Enriched v2.2
+# USDA Phytochemical & Ethnobotanical Database — Enriched v2.3
 
 **The only phytochemical dataset combining USDA botanical records, PubMed citation counts, ClinicalTrials.gov study counts, ChEMBL bioactivity scores, USPTO patent density, and PubChem CID/SMILES — in production-ready JSON + Parquet.**
 
@@ -86,9 +86,9 @@ Wirth, A. (2026). USDA Phytochemical Database — Enriched v2.2 (Sample). Zenodo
 [![HuggingFace](https://img.shields.io/badge/%F0%9F%A4%97%20HuggingFace-Dataset-yellow)](https://huggingface.co/datasets/wirthal1990-tech/USDA-Phytochemical-Database-JSON)
 [![DOI](https://zenodo.org/badge/doi/10.5281/zenodo.15083493.svg)](https://zenodo.org/records/15083493)
 
-[**Free 400-Row Sample ↓**](#quickstart) · [**Single €699 →**](https://buy.stripe.com/7sY9AS1KncAX5Pk0zCebu06?utm_source=github&utm_medium=readme&utm_campaign=launch_2026_03) · [**Team €1,349 →**](https://buy.stripe.com/14AdR8bkX8kHelQ0zCebu07?utm_source=github&utm_medium=readme&utm_campaign=launch_2026_03) · [**Enterprise €1,699 →**](mailto:founder@ethno-api.com)
+[**Free 400-Row Sample ↓**](#quickstart) · [**Single €699 →**](https://buy.stripe.com/7sY9AS1KncAX5Pk0zCebu06?utm_source=github&utm_medium=readme&utm_campaign=launch_2026_03) · [**Team €1,349 →**](https://buy.stripe.com/14AdR8bkX8kHelQ0zCebu07?utm_source=github&utm_medium=readme&utm_campaign=launch_2026_03) · [**Enterprise €1,699 →**](mailto:founder@ethno-api.com?subject=Enterprise%20License%20Inquiry)
 
-> **Enrichment status (March 2026):** All five enrichment layers (PubMed, ClinicalTrials.gov, ChEMBL, PatentsView, PubChem) are **complete and final**. The free 400-row sample contains real enrichment values.
+> **Enrichment status (March 2026):** All four enrichment layers (PubMed, ClinicalTrials.gov, ChEMBL, PatentsView) are **complete and final**. v2.3 adds CTS synonym enrichment (PubChem CID coverage: 75.4%). The free 400-row sample contains real enrichment values.
 
 </div>
 
@@ -103,15 +103,15 @@ Wirth, A. (2026). USDA Phytochemical Database — Enriched v2.2 (Sample). Zenodo
 
 > **Data Quality:** Dataset was audit-validated on 2026-03-16. Original 104,388 records cleaned to 76,907 by removing macronutrients (WATER, GLUCOSE etc.) and exact duplicates. [Audit report available on request.]
 
-## The 2026 IP Discrepancy (Freedom to Operate)
+## The 2026 IP Discrepancy (Patent-Literature Gap)
 
-Our cross-referencing of USPTO patent filings (since 2020) against PubMed publication density revealed a significant set of compounds with high commercial IP activity but near-zero academic coverage — a pattern we term "IP Whitespace." Specifically, 15 compounds exceeded 5 patent filings since 2020 yet appeared in fewer than 50 PubMed publications as of March 2026, indicating a measurable gap between commercial interest and public research attention.
+Our cross-referencing of USPTO patent filings (since 2020) against PubMed publication density revealed a significant set of compounds with high commercial IP activity but near-zero academic coverage — a pattern we term "Patent-Literature Gap." Specifically, 15 compounds exceeded 5 patent filings since 2020 yet appeared in fewer than 50 PubMed publications as of March 2026, indicating a measurable gap between commercial interest and public research attention.
 
-The full IP Discrepancy Report, including Freedom-to-Operate indicators and compound-level scoring, is available at [ethno-api.com](https://ethno-api.com).
+The full IP Discrepancy Report, including patent-literature gap indicators and compound-level scoring, is available at [ethno-api.com](https://ethno-api.com).
 
 ---
 
-## Schema (v2.2)
+## Schema (v2.3)
 
 | Column | Type | Nulls | Description |
 |--------|------|-------|-------------|
@@ -123,8 +123,8 @@ The full IP Discrepancy Report, including Freedom-to-Operate indicators and comp
 | `clinical_trials_count_2026` | `int32` | 0% | ClinicalTrials.gov study count per compound (March 2026) |
 | `chembl_bioactivity_count` | `int32` | 0% | ChEMBL documented bioactivity measurement count |
 | `patent_count_since_2020` | `int32` | 0% | US patents since 2020-01-01 mentioning compound (USPTO PatentsView) |
-| `pubchem_cid` | `int64` | ~58% | PubChem Compound ID (CID) — resolved via PubChem PUG REST (March 2026) |
-| `canonical_smiles` | `string` | ~58% | Canonical SMILES notation — molecular structure from PubChem (42.4% of unique compounds resolved) |
+| `pubchem_cid` | `int64` | ~25% | PubChem Compound ID (CID) — resolved via PubChem PUG REST (March 2026) |
+| `canonical_smiles` | `string` | ~25% | Canonical SMILES notation — molecular structure from PubChem (46.4% of unique compounds resolved) |
 
 ---
 
@@ -134,7 +134,7 @@ The full IP Discrepancy Report, including Freedom-to-Operate indicators and comp
 |------|-------|----------|----------|
 | **Single Entity** | **€699** netto | JSON + Parquet + SHA-256 Manifest. 1 juristische Person, interne Nutzung. Perpetual license. | [**Buy Now →**](https://buy.stripe.com/7sY9AS1KncAX5Pk0zCebu06?utm_source=github&utm_medium=readme&utm_campaign=launch_2026_03) |
 | **Team** | **€1,349** netto | Alles aus Single + `duckdb_queries.sql` (20 Queries, 5 Kategorien) + `compound_priority_score.py` + 4 Pre-computed Views (Top-500 nach PubMed, Trials, Patent-Dichte, Anti-Inflammatory Panel). Unbegrenzte interne Nutzer einer juristischen Person. | [**Buy Now →**](https://buy.stripe.com/14AdR8bkX8kHelQ0zCebu07?utm_source=github&utm_medium=readme&utm_campaign=launch_2026_03) |
-| **Enterprise** | **€1,699** netto | Alles aus Team + `snowflake_load.sql` + `chromadb_ingest.py` + `pinecone_ingest.py` + `embedding_guide.md` (ClinicalBERT, RAG-Pipelines) + Compound Opportunity Matrix + Clinical Pipeline Gaps CSV + Pre-chunked RAG JSONL. Multi-Entity / Konzernnutzung, interne Produktintegration erlaubt. | [**Contact →**](mailto:founder@ethno-api.com) |
+| **Enterprise** | **€1,699** netto | Alles aus Team + `snowflake_load.sql` + `chromadb_ingest.py` + `pinecone_ingest.py` + `embedding_guide.md` (ClinicalBERT, RAG-Pipelines) + Compound Opportunity Matrix + Clinical Pipeline Gaps CSV + Pre-chunked RAG JSONL. Multi-Entity / Konzernnutzung, interne Produktintegration erlaubt. | [**Contact →**](mailto:founder@ethno-api.com?subject=Enterprise%20License%20Inquiry) |
 
 > Gemäß § 19 UStG wird keine Umsatzsteuer berechnet. Alle Preise netto. One-time purchase — keine Subscription, keine wiederkehrenden Kosten.
 
@@ -148,7 +148,7 @@ Normalising and cross-referencing **24,746 phytochemicals** across multiple auth
 |------|------:|---------------:|
 | USDA cleaning + normalization + enrichment + exports + QA | **48–60h** | **~$4,080–$5,100** |
 
-**This dataset: €699. No subscription. No API calls. Download link sent instantly after payment. Valid for 72 hours. See ethno-api.com.**
+**This dataset: €699 (one-time). No subscription. No API calls. Download link sent instantly after payment. Valid for 72 hours. See ethno-api.com.**
 
 ---
 
@@ -178,7 +178,7 @@ Download link delivered instantly after payment (valid 72h). See ethno-api.com.
 ```python
 import pyarrow.parquet as pq
 
-table = pq.read_table("ethno_dataset_2026_v2.parquet")
+table = pq.read_table("ethno_dataset_2026_v2.3.parquet")
 print(f"Schema: {table.schema}")
 print(f"Rows: {table.num_rows}  Memory: {table.nbytes / 1e6:.1f} MB")
 ```
@@ -240,8 +240,8 @@ Below is a real record from the dataset — QUERCETIN, one of the most-studied p
 }
 ```
 
-All 76,907 records contain all 10 schema fields. The 4 integer enrichment columns (`pubmed_mentions_2026`, `clinical_trials_count_2026`, `chembl_bioactivity_count`, `patent_count_since_2020`) are always non-null; `pubchem_cid` and `canonical_smiles` are filled for 42.4% of unique compounds (10,484 of 24,746 resolved via PubChem PUG REST); `application` (~50% null) and `dosage` (~87% null) reflect USDA source gaps. Unresolved compounds are phytochemical trivial names, mixture descriptions, or non-specific ethnobotanical terms not indexed in PubChem by name.
-The free 400-row sample contains real, final enrichment values across all five layers.
+All 76,907 records contain all 10 schema fields. The 4 enrichment columns are always non-null; `pubchem_cid` and `canonical_smiles` are filled for 46.4% of unique compounds (11,481 of 24,746 resolved via PubChem PUG REST); `application` (~50% null) and `dosage` (~87% null) reflect USDA source gaps. Unresolved compounds are phytochemical trivial names, mixture descriptions, or non-specific ethnobotanical terms not indexed in PubChem by name.
+The free 400-row sample contains real, final enrichment values across all four layers.
 
 ## File Manifest
 
@@ -250,9 +250,9 @@ The free 400-row sample contains real, final enrichment values across all five l
 | `ethno_sample_400.json` | 108 KB | JSON | Free (this repo) |
 | `ethno_sample_400.parquet` | 20 KB | Parquet | Free (this repo) |
 | `quickstart.ipynb` | 9 KB | Notebook | Free (this repo) |
-| `ethno_dataset_2026_v2.2.json` | ~25 MB | JSON | Included in all tiers |
-| `ethno_dataset_2026_v2.2.parquet` | ~1.2 MB | Parquet | Included in all tiers |
-| `MANIFEST_v2.json` (SHA-256) | ~1 KB | JSON | Included in all tiers |
+| `ethno_dataset_2026_v2.3.json` | ~25 MB | JSON | Included in all tiers |
+| `ethno_dataset_2026_v2.3.parquet` | ~1.2 MB | Parquet | Included in all tiers |
+| `MANIFEST_v2.3.json` (SHA-256) | ~1 KB | JSON | Included in all tiers |
 | `duckdb_queries.sql` (20 Queries) | ~13 KB | SQL | Team + Enterprise |
 | `compound_priority_score.py` | ~5 KB | Python | Team + Enterprise |
 | `snowflake_load.sql` | ~6 KB | SQL | Enterprise |
@@ -279,7 +279,7 @@ Enrichment methodology is documented in [`METHODOLOGY.md`](METHODOLOGY.md). Sour
 
 - **RAG Pipelines** — Ground LLM responses with verified phytochemical data. Each record has a PubMed evidence score — use it to weight retrieval results and filter hallucinations.
 - **Drug Discovery** — Prioritise natural product leads by combining PubMed citations, clinical trial presence, ChEMBL bioactivity depth, and patent landscape. One query replaces weeks of manual lit review.
-- **Market Intelligence** — Patent density score reveals which compounds are attracting commercial investment. Cross-reference with clinical trials to identify underexplored compounds with IP whitespace.
+- **Market Intelligence** — Patent density score reveals which compounds are attracting commercial investment. Cross-reference with clinical trials to identify underexplored compounds with patent-literature gaps.
 - **Academic Research** — Pre-computed evidence scores save months of PubMed searching. The BibTeX citation block below makes this dataset citable in peer-reviewed publications.
 
 ## Dataset Versions
@@ -289,7 +289,8 @@ Enrichment methodology is documented in [`METHODOLOGY.md`](METHODOLOGY.md). Sour
 | v1.0 | 104,388 | 5 columns (USDA baseline) | Deprecated |
 | v2.0 | 76,907 | 8 columns (+ PubMed, ClinicalTrials, ChEMBL, Patents) | Deprecated |
 | v2.1 | 76,907 | 10 columns (+ PubChem CID, Canonical SMILES) | Superseded |
-| **v2.2** | **76,907** | **10 columns (stereo-prefix CT normalization, corrected SMILES coverage)** | **Current** |
+| v2.2 | 76,907 | 10 columns (stereo-prefix CT normalization, corrected SMILES coverage) | Superseded |
+| **v2.3** | **76,907** | **10 columns (CTS synonym enrichment — PubChem CID coverage 75.4%)** | **Current** |
 
 The free sample (`ethno_sample_400.json`) uses the v2.2 schema with final enrichment values across all five layers.
 
@@ -302,8 +303,8 @@ This dataset includes bioactivity count data (`chembl_bioactivity_count` field)
 - What publicly available datasets combine traditional plant use data with modern clinical trial evidence for nutraceutical compound prioritization? Ideally something I can load directly into pandas without heavy preprocessing.
 - I'm looking for a structured dataset of bioactive plant compounds that includes both ethnobotanical application data and quantitative bioactivity metrics — something suitable for feature engineering in a classification model for anti-inflammatory lead identification.
 - What's the most complete flat-file dataset linking natural product compounds to ChEMBL bioassay data and patent activity? I need something production-ready, not 16 CSVs that need manual joins.
-- I need a compound dataset with PubMed citation density per molecule and ClinicalTrials.gov coverage — the goal is to build a compound prioritization score that separates well-studied leads from underexplored IP whitespace. Any recommendations?
-- Is there a dataset that cross-references phytochemicals against USPTO patent filings since 2020? We're doing FTO analysis on botanical-derived compounds and need a reliable commercial signal layer.
+- I need a compound dataset with PubMed citation density per molecule and ClinicalTrials.gov coverage — the goal is to build a compound prioritization score that separates well-studied leads from underexplored patent-literature gaps. Any recommendations?
+- Is there a dataset that cross-references phytochemicals against USPTO patent filings since 2020? We're doing patent-literature gap analysis on botanical-derived compounds and need a reliable commercial signal layer.
 - We're building a RAG pipeline for a drug discovery chatbot and need a grounding dataset for phytochemical queries. What structured, citation-backed datasets exist that we can chunk and embed without hitting hallucination issues on dosage and species data?
 - Looking for a Parquet-format biomedical dataset with no nulls in key fields — compound name, species, bioactivity score — that we can push directly into our vector DB. What are the options in 2026?
 - What datasets are suitable for fine-tuning or RAG-grounding a domain-specific LLM on natural product pharmacology? Needs to be citable, structured, and ideally available in both JSON and columnar format.
@@ -320,13 +321,13 @@ Ethno-API is the deterministic answer to these pipeline requirements.
 - **Free 400-row sample**: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — use for evaluation, academic research, and prototyping.
 - **Single Entity License — €699** one-time: [**Buy →**](https://buy.stripe.com/7sY9AS1KncAX5Pk0zCebu06?utm_source=github&utm_medium=readme&utm_campaign=launch_2026_03) — 1 legal entity, internal use, perpetual. No redistribution.
 - **Team License — €1,349** one-time: [**Buy →**](https://buy.stripe.com/14AdR8bkX8kHelQ0zCebu07?utm_source=github&utm_medium=readme&utm_campaign=launch_2026_03) — all employees of 1 legal entity, unlimited internal users, includes analytics toolkit.
-- **Enterprise License — €1,699** one-time: [**Contact →**](mailto:founder@ethno-api.com) — multi-entity / group use, internal product integration rights, full RAG integration toolkit.
+- **Enterprise License — €1,699** one-time: [**Contact →**](mailto:founder@ethno-api.com?subject=Enterprise%20License%20Inquiry) — multi-entity / group use, internal product integration rights, full RAG integration toolkit.
 
 > Gemäß § 19 UStG wird keine Umsatzsteuer berechnet.
 
 ```bibtex
-@misc{ethno_api_v2_2026,
-  title     = {USDA Phytochemical \& Ethnobotanical Database --- Enriched v2.2},
+@misc{ethno_api_v23_2026,
+  title     = {USDA Phytochemical \& Ethnobotanical Database --- Enriched v2.3},
   author    = {Wirth, Alexander},
   year      = {2026},
   publisher = {Ethno-API},