{"id":"W6963030529","doi":"10.17632/gc423hprcs","title":"Regulatory Compliance Ceiling Effect/Diminishing Returns, Regulatory Compliance and Quality Indicators Scales","year":2023,"lang":"en","type":"dataset","venue":"Mendeley Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Compliance (psychology); Ceiling (cloud); Quality (philosophy); Scale (ratio); Consistency (knowledge bases); Predictive power; Ceiling effect","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":[0.0155008,0.0003049329,0.0006424711,0.007032993,0.001479202,0.00182309,0.002004569,0.0003035236,0.004735917],"category_scores_gemma":[0.06757326,0.0003219635,0.0005945573,0.01046281,0.00128772,0.0009249512,0.001717725,0.0008549592,0.0005902745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0130126,"about_ca_system_score_gemma":0.02145828,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.535152,"about_ca_topic_score_gemma":0.6552566,"domain_scores_codex":[0.967003,0.004118311,0.002954963,0.001046349,0.02368421,0.001193188],"domain_scores_gemma":[0.9115067,0.01939379,0.01508717,0.007453216,0.04451576,0.002043415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004068735,0.000626229,0.719943,0.0008699915,0.0001732132,0.0001172854,0.003939238,0.00245301,0.0009844109,0.005323228,0.03162194,0.2335415],"study_design_scores_gemma":[0.00002264605,0.0001110469,0.9837254,0.00008893583,0.00002434083,0.00002723297,0.0009080608,0.001025286,0.0004680332,0.0004062298,0.01316218,0.00003066207],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.7713953,0.0009513933,0.02529691,0.001111473,0.0001247873,0.007664362,0.08261347,0.001073218,0.1097692],"genre_scores_gemma":[0.9058937,0.000544539,0.0331452,0.0002028814,0.00003499903,0.004709129,0.04555402,0.0001438376,0.009771589],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.535152,"threshold_uncertainty_score":0.9351711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1916522797575967,"score_gpt":0.3940082864174128,"score_spread":0.2023560066598162,"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."}}