{"id":"W2922013545","doi":"10.1126/science.aaw3613","title":"Best supporting actors","year":2019,"lang":"en","type":"article","venue":"Science","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Skeletal muscle; Stem cell; Cell biology; Business; Biology; Computational biology; Anatomy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002683,0.001328473,0.001231581,0.001955842,0.001476384,0.009034774,0.001385314,0.005827549,0.6631595],"category_scores_gemma":[0.02706974,0.0004590509,0.0007698481,0.0009979365,0.00071366,0.003526042,0.004641147,0.003432082,0.5217972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001426467,"about_ca_system_score_gemma":0.005127287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000707435,"about_ca_topic_score_gemma":0.002014702,"domain_scores_codex":[0.9978275,0.0003597312,0.0001606959,0.0003350896,0.000904663,0.0004124024],"domain_scores_gemma":[0.983326,0.002251854,0.0008721456,0.000708414,0.00445492,0.008386774],"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":[0.00006140853,0.00001649381,0.0001727917,0.0001389662,0.000005415906,0.00009631672,0.00001540438,0.00003643783,0.0001486185,0.002210292,0.9210508,0.07604708],"study_design_scores_gemma":[0.00003353365,0.00001918298,0.0001316297,0.0003074046,0.000007644352,0.000232275,0.00006674358,0.00005555434,0.0001330167,0.003522964,0.9954807,0.000009419748],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.001240703,0.03148128,0.006587104,0.186123,0.1735272,0.0004148845,0.01102321,0.002994755,0.5866078],"genre_scores_gemma":[0.01195775,0.02030652,0.009026994,0.0540986,0.05265264,0.0006922698,0.00684515,0.002213654,0.8422065],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.6631595,"threshold_uncertainty_score":0.4804621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006007739653939785,"score_gpt":0.276574086230775,"score_spread":0.2705663465768351,"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."}}