{"id":"W1974966065","doi":"10.1016/j.neuron.2015.03.016","title":"Casting a Genome-wide Net for Learning Mutants","year":2015,"lang":"en","type":"letter","venue":"Neuron","topic":"Zebrafish Biomedical Research Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia","funders":"","keywords":"Mutant; Genome; Computational biology; Neuroscience; Biology; Computer science; Psychology; Genetics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002451709,0.0002161061,0.0001929547,0.00006863774,0.0001075264,0.00004974908,0.0004199333,0.0005841046,0.00002599359],"category_scores_gemma":[0.002156845,0.0002185735,0.0001048266,0.00009830276,0.00009883661,0.000001803905,0.000225408,0.0009405669,0.00006091454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003530128,"about_ca_system_score_gemma":0.0002597727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001091875,"about_ca_topic_score_gemma":0.000006075534,"domain_scores_codex":[0.9981848,0.00009497024,0.0002124503,0.0006005034,0.0003502422,0.0005570629],"domain_scores_gemma":[0.9990019,0.0001146987,0.0001200081,0.0004233074,0.0001830528,0.0001570517],"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":[0.0000197461,0.00001076104,0.00005238055,0.000067389,0.00002471318,0.0000331909,0.000006351625,0.000009085319,0.0497208,5.281601e-7,0.9475923,0.002462715],"study_design_scores_gemma":[0.000292276,0.0003793044,0.0001224367,0.00001144024,0.00001660333,0.00001683732,0.000003866783,0.00009785897,0.001509998,0.00004876098,0.9973021,0.0001985157],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.05679817,0.001972388,0.01675323,0.904147,0.001003008,0.004570465,0.001021796,0.0002479925,0.01348591],"genre_scores_gemma":[0.03565698,0.0003254464,0.002316519,0.8819668,0.02026084,0.001342376,0.01812536,0.0005046136,0.03950112],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.04970977,"threshold_uncertainty_score":0.891317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.032970347774219,"score_gpt":0.3026044592812567,"score_spread":0.2696341115070377,"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."}}