Add entry (688638f5) to requests.jsonl

requests.jsonl

@@ -29,3 +29,4 @@
 {"id": "bcfd016d-a66a-43ea-aa5e-56e6493947dd", "type": "dataset", "title": "AINovice2005/carbon-cpu-enriched-sequences", "description": "A CPU-enriched subset of the carbon pretraining corpus (eukaryote_generator), combining original source fields with normalized sequences and row-level features for quality analysis, GPU enrichment and embedding generation.", "submitted_at": "2026-10-26T08:02:33.221Z", "source": "huggingscience.co", "status": "pending", "entry_id": "ainovice2005-carbon-cpu-enriched-sequences", "slug": "AINovice2005/carbon-cpu-enriched-sequences", "org_id": "AINovice2005", "entry_type": "Genomics", "tags": ["biology", "biotechnology"]}
 {"id": "008f9639-a334-45c9-a113-2d7b7046e5ba", "type": "dataset", "title": "AINovice2005/carbon-embeddings", "description": "AINovice2005/carbon-embeddings is a derived dataset from the sampled subset of carbon-cpu-enriched-sequences containing dense vector embeddings of biological sequence records.\n\nEach row corresponds to a source sequence identified by record_id. The dataset retains the sequence's position within the processed corpus through start and end and provides a numerical embedding representing the sequence in the embedding model's learned representation space.\n\nThe dataset is intended for downstream embedding-based analysis, including similarity search, clustering, retrieval and visualization.", "submitted_at": "2026-10-26T08:03:39.653Z", "source": "huggingscience.co", "status": "pending", "entry_id": "ainovice2005-carbon-embeddings", "slug": "AINovice2005/carbon-embeddings", "org_id": "AINovice2005", "entry_type": "Genomics", "tags": ["biology", "biotechnology"]}
 {"id": "4d2eceec-18f4-438c-b9a9-33fe11aae896", "type": "dataset", "title": "AINovice2005/carbon-likelihood-stats", "description": "AINovice2005/carbon-likelihood-stats is a model-enriched dataset derived from the Carbon genomic corpus, containing sequence-level likelihood statistics for 251,427 sequence regions.\n\nEach row links a source sequence record to its corresponding region in the processed/tokenized Carbon corpus using record_id, start, and end. The dataset summarizes both the model's overall likelihood of the observed sequence and the variation in token-level model confidence within that sequence.\n\nThe dataset contains aggregate likelihood measures including mean_log_prob, sum_log_prob, and perplexity, together with local likelihood statistics such as min_token_logprob, argmin_position, and per_token_logprob_std. supervised_position_count records the number of token positions that contributed to the likelihood calculation. The start and end fields represent corpus coordinates.", "submitted_at": "2026-10-26T08:04:20.618Z", "source": "huggingscience.co", "status": "pending", "entry_id": "ainovice2005-carbon-likelihood-stats", "slug": "AINovice2005/carbon-likelihood-stats", "org_id": "AINovice2005", "entry_type": "Genomics", "tags": ["biology", "biotechnology"]}
+{"id": "688638f5-57c1-407a-9cb9-ee664af5dde8", "type": "blog", "title": "From Genomic Sequences to Taxonomic IDs (Part 1): Building a Scalable Enrichment Pipeline for the Carbon Pretraining Corpus", "description": "Raw genomic sequences hold biological signal that's hard to read without context. We built a CPU-only pipeline that enriches the carbon-pretraining-corpus with sequence length, GC content, coding status, and taxonomy with no Carbon model involved. The output: a 32.4M-record enriched corpus, providing a structured foundation for biological analysis.", "submitted_at": "2026-10-26T08:05:33.343Z", "source": "huggingscience.co", "status": "pending", "entry_id": "ainovice2005-hf-enrichment-pipeline", "slug": "AINovice2005/hf-enrichment-pipeline", "link": "https://huggingface.co/blog/AINovice2005/hf-enrichment-pipeline", "date": "2026-09-24", "tags": ["biology", "biotechnology"]}