Datasets:

wirthal1990-tech
/

USDA-Phytochemical-Database-JSON

@@ -159,32 +159,7 @@
    "cell_type": "markdown",
    "id": "cell-07",
    "metadata": {},
-   "source": [
-    "## What's Included in Each Tier\n",
-    "\n",
-    "### Team License (€1,349) — adds to Single:\n",
-    "| File | Description |\n",
-    "|------|-------------|\n",
-    "| `duckdb_queries.sql` | 20 production-ready queries across 5 categories (compound discovery, evidence scoring, species analysis, application intelligence, IP/pipeline) |\n",
-    "| `compound_priority_score.py` | Combined evidence score calculator across all 4 layers |\n",
-    "| `top500_by_pubmed.parquet` | Pre-computed Top 500 compounds by PubMed score |\n",
-    "| `top500_by_trials.parquet` | Pre-computed Top 500 by ClinicalTrials count |\n",
-    "| `top500_by_patent_density.parquet` | Pre-computed Top 500 by patent density |\n",
-    "| `anti_inflammatory_panel.parquet` | All anti-inflammatory application records |\n",
-    "\n",
-    "### Enterprise License (€1,699) — adds to Team:\n",
-    "| File | Description |\n",
-    "|------|-------------|\n",
-    "| `snowflake_load.sql` | Drop-in Snowflake import script (Stage + COPY INTO + Verify) |\n",
-    "| `chromadb_ingest.py` | ChromaDB vector ingest with batch upload, --resume, verification |\n",
-    "| `pinecone_ingest.py` | Pinecone ingest supporting OpenAI, sentence-transformers, Pinecone inference |\n",
-    "| `embedding_guide.md` | ClinicalBERT, RAG pipeline templates, cost benchmarks |\n",
-    "| `compound_opportunity_matrix.csv` | Ranked compound candidates: high bioactivity × low patent density |\n",
-    "| `clinical_pipeline_gaps.csv` | High-PubMed, low-trial compounds: drug discovery pipeline gaps |\n",
-    "| `ethno_rag_chunks.jsonl` | Pre-chunked JSONL for direct LLM embedding (ChromaDB / Pinecone) |\n",
-    "\n",
-    "→ **Purchase full dataset:** [ethno-api.com](https://ethno-api.com)\n"
-   ]
   },
   {
    "cell_type": "code",
@@ -209,25 +184,7 @@
    "cell_type": "markdown",
    "id": "cell-09",
    "metadata": {},
-   "source": [
-    "## Citation\n",
-    "\n",
-    "```bibtex\n",
-    "@misc{ethno_api_v2_2026,\n",
-    "  title     = {USDA Phytochemical \\& Ethnobotanical Database --- Enriched v2.0},\n",
-    "  author    = {Wirth, Alexander},\n",
-    "  year      = {2026},\n",
-    "  publisher = {Ethno-API},\n",
-    "  url       = {https://ethno-api.com},\n",
-    "  note      = {104,388 records, 24,771 unique chemicals, 2,315 plant species,\n",
-    "               8-column schema with PubMed, ClinicalTrials, ChEMBL, and PatentsView enrichment}\n",
-    "}\n",
-    "```\n",
-    "\n",
-    "**Links:** [ethno-api.com](https://ethno-api.com) · ",
-    "[GitHub](https://github.com/wirthal1990-tech/USDA-Phytochemical-Database-JSON) · ",
-    "[HuggingFace](https://huggingface.co/datasets/wirthal1990-tech/USDA-Phytochemical-Database-JSON)\n"
-   ]
   }
  ]
 }

    "cell_type": "markdown",
    "id": "cell-07",
    "metadata": {},
+   "source": "## What's Included in Each Tier\n\n### Team License (€1,349) — adds to Single:\n| File | Description |\n|------|-------------|\n| `duckdb_queries.sql` | 20 production-ready queries across 5 categories (compound discovery, evidence scoring, species analysis, application intelligence, IP/pipeline) |\n| `compound_priority_score.py` | Combined evidence score calculator across all 4 layers |\n| `top500_by_pubmed.parquet` | Pre-computed Top 500 compounds by PubMed score |\n| `top500_by_trials.parquet` | Pre-computed Top 500 by ClinicalTrials count |\n| `top500_by_patent_density.parquet` | Pre-computed Top 500 by patent density |\n| `anti_inflammatory_panel.parquet` | All anti-inflammatory application records |\n\n### Enterprise License (€1,699) — adds to Team:\n| File | Description |\n|------|-------------|\n| `snowflake_load.sql` | Drop-in Snowflake import script (Stage + COPY INTO + Verify) |\n| `chromadb_ingest.py` | ChromaDB vector ingest with batch upload, --resume, verification |\n| `pinecone_ingest.py` | Pinecone ingest supporting OpenAI, sentence-transformers, Pinecone inference |\n| `embedding_guide.md` | ClinicalBERT, RAG pipeline templates, cost benchmarks |\n| `compound_opportunity_matrix.csv` | Ranked compound candidates: high bioactivity × low patent density |\n| `clinical_pipeline_gaps.csv` | High-PubMed, low-trial compounds: drug discovery pipeline gaps |\n| `ethno_rag_chunks.jsonl` | Pre-chunked JSONL for direct LLM embedding (ChromaDB / Pinecone) |\n\n→ **Purchase full dataset:** [ethno-api.com](https://ethno-api.com)\n\n\n---\n\n**→ Purchase the full dataset:**\n\n[**Single Entity €699 →**](https://buy.stripe.com/00w6oGgFh58v6Toeqsebu02) &nbsp;&nbsp;[**Team €1.349 →**](https://buy.stripe.com/dRm7sK9cP1Wj0v06Y0ebu03) &nbsp;&nbsp;[**Enterprise €1.699 →**](https://buy.stripe.com/dRm28q0Gj1WjdhM6Y0ebu04)\n"
   },
   {
    "cell_type": "code",
    "cell_type": "markdown",
    "id": "cell-09",
    "metadata": {},
+   "source": "## Citation\n\n```bibtex\n@misc{ethno_api_v2_2026,\n  title     = {USDA Phytochemical \\& Ethnobotanical Database --- Enriched v2.0},\n  author    = {Wirth, Alexander},\n  year      = {2026},\n  publisher = {Ethno-API},\n  url       = {https://ethno-api.com},\n  note      = {104,388 records, 24,771 unique chemicals, 2,315 plant species,\n               8-column schema with PubMed, ClinicalTrials, ChEMBL, and PatentsView enrichment}\n}\n```\n\n**Links:** [ethno-api.com](https://ethno-api.com) · [GitHub](https://github.com/wirthal1990-tech/USDA-Phytochemical-Database-JSON) · [HuggingFace](https://huggingface.co/datasets/wirthal1990-tech/USDA-Phytochemical-Database-JSON)\n\n\n---\n\n## Purchase Full Dataset\n\n| Tier | Price | |\n|------|-------|---|\n| Single Entity | €699 | [**Buy →**](https://buy.stripe.com/00w6oGgFh58v6Toeqsebu02) |\n| Team | €1.349 | [**Buy →**](https://buy.stripe.com/dRm7sK9cP1Wj0v06Y0ebu03) |\n| Enterprise | €1.699 | [**Buy →**](https://buy.stripe.com/dRm28q0Gj1WjdhM6Y0ebu04) |\n\n> Gemäß § 19 UStG keine Umsatzsteuer.\n"
   }
  ]
 }