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fix: Cell-01 price notation + Cell-07 duplicate link removed

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  1. quickstart.ipynb +2 -15
quickstart.ipynb CHANGED
@@ -17,20 +17,7 @@
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  "cell_type": "markdown",
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  "id": "cell-01",
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  "metadata": {},
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- "source": [
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- "# USDA Phytochemical & Ethnobotanical Database — Enriched v2.0\n",
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- "\n",
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- "**104,388 records · 24,771 compounds · 2,315 species · 4 enrichment layers**\n",
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- "\n",
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- "| Tier | Price | Includes |\n",
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- "|------|-------|----------|\n",
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- "| **Single Entity** | €699 | JSON + Parquet + SHA-256 Manifest |\n",
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- "| **Team** | €1,349 | + `duckdb_queries.sql` (20 queries) + `compound_priority_score.py` + 4 Pre-computed Views |\n",
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- "| **Enterprise** | €1,699 | + `snowflake_load.sql` + `chromadb_ingest.py` + `pinecone_ingest.py` + `embedding_guide.md` + Opportunity Matrix |\n",
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- "\n",
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- "**Full dataset:** [ethno-api.com](https://ethno-api.com) · ",
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- "**This notebook runs on the free 400-row sample.**\n"
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- ]
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  },
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  {
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  "cell_type": "code",
@@ -159,7 +146,7 @@
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  "cell_type": "markdown",
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  "id": "cell-07",
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  "metadata": {},
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- "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)   [**Team €1.349 →**](https://buy.stripe.com/dRm7sK9cP1Wj0v06Y0ebu03)   [**Enterprise €1.699 →**](https://buy.stripe.com/dRm28q0Gj1WjdhM6Y0ebu04)\n"
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  },
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  {
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  "cell_type": "code",
 
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  "cell_type": "markdown",
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  "id": "cell-01",
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  "metadata": {},
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+ "source": "# USDA Phytochemical & Ethnobotanical Database — Enriched v2.0\n\n**104,388 records · 24,771 compounds · 2,315 species · 4 enrichment layers**\n\n| Tier | Price | Includes |\n|------|-------|----------|\n| **Single Entity** | [€699](https://buy.stripe.com/00w6oGgFh58v6Toeqsebu02) | JSON + Parquet + SHA-256 Manifest |\n| **Team** | [€1.349](https://buy.stripe.com/dRm7sK9cP1Wj0v06Y0ebu03) | + `duckdb_queries.sql` (20 queries) + `compound_priority_score.py` + 4 Pre-computed Views |\n| **Enterprise** | [€1.699](https://buy.stripe.com/dRm28q0Gj1WjdhM6Y0ebu04) | + `snowflake_load.sql` + `chromadb_ingest.py` + `pinecone_ingest.py` + `embedding_guide.md` + Opportunity Matrix |\n\n**Full dataset:** [ethno-api.com](https://ethno-api.com) · **This notebook runs on the free 400-row sample.**\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
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  },
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  {
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  "cell_type": "code",
 
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  "cell_type": "markdown",
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  "id": "cell-07",
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  "metadata": {},
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+ "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---\n\n**→ Purchase the full dataset:**\n\n[**Single Entity €699 →**](https://buy.stripe.com/00w6oGgFh58v6Toeqsebu02)   [**Team €1.349 →**](https://buy.stripe.com/dRm7sK9cP1Wj0v06Y0ebu03)   [**Enterprise €1.699 →**](https://buy.stripe.com/dRm28q0Gj1WjdhM6Y0ebu04)\n"
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  },
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  {
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  "cell_type": "code",