{"id":"W7070548394","doi":"","title":"Ontario PublicAccounts 1415 Vol1","year":2019,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002095245,0.0003808318,0.0003745027,0.00007480654,0.00004101278,0.00006816205,0.0005040527,0.0007077627,0.2488879],"category_scores_gemma":[0.00014816,0.000379355,0.0001860853,0.000005904215,0.00009309015,3.286922e-8,0.0002176593,0.0003530767,0.0209044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005149139,"about_ca_system_score_gemma":0.0001296427,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02554665,"about_ca_topic_score_gemma":0.03152984,"domain_scores_codex":[0.9984144,0.00004401056,0.000597911,0.0002273251,0.0003883854,0.0003279869],"domain_scores_gemma":[0.9983013,0.00001915437,0.0007094715,0.0007071458,0.0001576367,0.0001052844],"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":[0.00005196471,0.00002880585,0.00007658065,0.000344276,0.0001002483,0.000001669785,0.00007136666,0.0001170831,0.000001637083,0.00001630859,0.9984732,0.0007169093],"study_design_scores_gemma":[0.0005289116,0.0002064632,0.00003056551,0.0001077717,0.00003634311,0.00004654321,0.00002791146,0.00001718568,0.00001989864,0.000001864077,0.9985742,0.0004023271],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000145656,0.0001704498,0.000001849053,0.00007805097,0.0004214142,0.0004452284,0.0001276336,0.00006525447,0.9985445],"genre_scores_gemma":[0.0003525715,0.00009623037,0.001628324,0.0005206984,0.0001920262,0.00001179516,0.001191801,0.0001385211,0.995868],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2279835,"threshold_uncertainty_score":0.9998658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004067289663228114,"score_gpt":0.183502356087893,"score_spread":0.1794350664246649,"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."}}