{"id":"W7066065766","doi":"","title":"A Framework for Regulatory Excellence","year":2015,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Excellence; Regulator; Regulatory reform; Regulatory state; Master regulator","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04538134,0.001626257,0.001539049,0.004588346,0.01054094,0.02169901,0.004093091,0.01540409,0.01109627],"category_scores_gemma":[0.04310985,0.0007601691,0.002013237,0.002878464,0.07997319,0.02516365,0.01214405,0.01436873,0.003049799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01884312,"about_ca_system_score_gemma":0.02081703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008647292,"about_ca_topic_score_gemma":0.004321829,"domain_scores_codex":[0.9514875,0.02636452,0.001955944,0.007313607,0.008502586,0.004375846],"domain_scores_gemma":[0.9732079,0.01493968,0.001891831,0.003071055,0.004916268,0.001973219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000001285751,0.000001918428,0.00001442303,0.000007520778,0.000001064202,0.000006678811,0.0001406477,0.00007873951,0.000006057124,0.9981946,0.0009993599,0.0005477889],"study_design_scores_gemma":[0.00001010912,0.000007757907,0.00003789184,0.00006545213,0.000002584725,0.00001991632,0.0002605484,0.0002706269,0.00003147597,0.9656167,0.03366802,0.000008916675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.004193707,0.007335756,0.1440246,0.2097887,0.002222682,0.0002365845,0.0001772443,0.0002383009,0.6317824],"genre_scores_gemma":[0.7822559,0.006802244,0.07285548,0.06139779,0.004781398,0.001935562,0.0002375686,0.0004381097,0.06929585],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04538134,"threshold_uncertainty_score":0.2400023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01777021943980322,"score_gpt":0.2807085241965123,"score_spread":0.2629383047567091,"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."}}