{"id":"W4210914372","doi":"10.1093/genetics/iyac003","title":"WormBase in 2022—data, processes, and tools for analyzing <i>Caenorhabditis elegans</i>","year":2022,"lang":"en","type":"article","venue":"Genetics","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":311,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"U.S. National Library of Medicine; National Human Genome Research Institute; Medical Research Council","keywords":"Caenorhabditis elegans; Biology; Workflow; Genomics; Data science; Data curation; Genome; Alliance; Caenorhabditis; Computational biology; Genetics; Computer science; Database; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008315421,0.003140197,0.003553296,0.01114863,0.002110801,0.007602394,0.006194105,0.003277401,0.03596852],"category_scores_gemma":[0.02055541,0.002194976,0.001910142,0.01096357,0.001047378,0.006936772,0.007925316,0.003859636,0.05004877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001628856,"about_ca_system_score_gemma":0.008930659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01012094,"about_ca_topic_score_gemma":0.01233513,"domain_scores_codex":[0.9971032,0.0004440455,0.0006301512,0.0004776528,0.001032845,0.0003122248],"domain_scores_gemma":[0.9912192,0.002185664,0.001024442,0.002143972,0.002025858,0.001400717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004496055,0.00006737323,0.001331722,0.003277654,0.0002292078,0.0002149743,0.0002368868,0.0007748856,0.004951423,0.008983684,0.9378304,0.04165216],"study_design_scores_gemma":[0.0001098493,0.00002767634,0.001838437,0.0005761316,0.0001058982,0.0001560276,0.0000680937,0.0009912164,0.0029621,0.005077407,0.9879819,0.0001052357],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.001520443,0.002328423,0.04466021,0.001537481,0.001216663,0.0005825417,0.8489813,0.08826835,0.01090475],"genre_scores_gemma":[0.002655345,0.001397582,0.04450776,0.0009161359,0.0001432373,0.0008769226,0.9361714,0.01101005,0.002321521],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03596852,"threshold_uncertainty_score":0.1203266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02150787986185723,"score_gpt":0.2534754082379426,"score_spread":0.2319675283760854,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}