{"id":"W2950280012","doi":"10.1016/j.cell.2019.05.039","title":"Next-Gen Learning: The C. elegans Approach","year":2019,"lang":"en","type":"letter","venue":"Cell","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Biology; Caenorhabditis elegans; Genetics; Computational biology; Evolutionary biology; 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":[0.00305925,0.0006765418,0.0006945262,0.000500345,0.001528831,0.002137944,0.001428554,0.01318291,0.008279241],"category_scores_gemma":[0.007935036,0.0004208303,0.0005096212,0.0002180536,0.002941053,0.00295935,0.001237923,0.01733856,0.004775447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001672376,"about_ca_system_score_gemma":0.001084167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001472091,"about_ca_topic_score_gemma":0.003477971,"domain_scores_codex":[0.9989914,0.0002352842,0.00005936827,0.0001495992,0.0004636899,0.0001005023],"domain_scores_gemma":[0.9965899,0.002168156,0.0001372308,0.0002242765,0.0004188743,0.0004615982],"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":[0.0003369744,0.00006576497,0.0003053971,0.0001372499,0.00003875965,0.0006859444,0.0000412562,0.0003369734,0.002241615,0.03821788,0.8579382,0.09965406],"study_design_scores_gemma":[0.0001882532,0.0001517427,0.0005032793,0.000173203,0.00003186832,0.001245138,0.00006845581,0.00195692,0.003107069,0.07121697,0.9212827,0.00007440792],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001082199,0.02300178,0.007360999,0.9018068,0.05142951,0.00004264772,0.0001420057,0.0003578114,0.01477632],"genre_scores_gemma":[0.02428097,0.02906631,0.006773167,0.8150653,0.06697388,0.0002460254,0.0001020364,0.0001451378,0.05734722],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01318291,"threshold_uncertainty_score":0.02769679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01410717381773101,"score_gpt":0.2034554142114455,"score_spread":0.1893482403937145,"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."}}