Add entry (b7d9f700) to requests.jsonl

requests.jsonl

@@ -30,3 +30,4 @@
 {"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"]}
+{"id": "b7d9f700-44b9-460a-bb2c-8b7185a52bce", "type": "dataset", "title": "proxima-fusion/coilstellaration", "description": "CoilStellaration is a dataset of optimized stellarator coilsets for 14,496 plasma boundaries from ConStellaration, together with a benchmark for models that design coils.\n\nEach sample pairs a plasma boundary with a randomly sampled set of engineering requirements, such as how far the coils must stay from each other and from the plasma. For every sample we designed a coilset with REGCOIL and, for two thirds of them, refined it with DESC. We then measured how accurately each coilset reproduces the plasma's magnetic field and how buildable it is.", "submitted_at": "2026-11-12T09:10:29.134Z", "source": "huggingscience.co", "status": "pending", "entry_id": "proxima-fusion-coilstellaration", "slug": "proxima-fusion/coilstellaration", "org_id": "proxima-fusion", "entry_type": "Fusion Physics", "tags": ["physics", "energy", "benchmark"]}