{"id":"W3081577969","doi":"10.3138/9781487534042-017","title":"Supplementary Information on Quantitative and Qualitative Methods: Ontario Component","year":2020,"lang":"en","type":"book-chapter","venue":"University of Toronto Press eBooks","topic":"Historical and modern epidemiology studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Component (thermodynamics); Computer science; Physics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006038792,0.001507986,0.001231387,0.007051561,0.002810177,0.002606715,0.00183884,0.00101667,0.8241915],"category_scores_gemma":[0.04274717,0.001242178,0.0008649506,0.01320771,0.0008430922,0.00164517,0.001978957,0.001105274,0.324965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01296274,"about_ca_system_score_gemma":0.0522726,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4191971,"about_ca_topic_score_gemma":0.6732326,"domain_scores_codex":[0.9959745,0.0008462156,0.0004691238,0.0004182892,0.001884821,0.0004071288],"domain_scores_gemma":[0.9477597,0.01642977,0.001185112,0.003897206,0.02898882,0.001739431],"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":[0.0000303359,0.00002184572,0.0002857925,0.0004423247,0.000002356083,0.00001086312,0.0001359505,0.00005556761,0.00007492165,0.0008990546,0.9768543,0.02118678],"study_design_scores_gemma":[0.0000827131,0.00002483943,0.006711128,0.0006078738,0.00001256374,0.00004383669,0.0004485417,0.0002652818,0.0004391902,0.002360548,0.9889706,0.00003287374],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001094022,0.0004546497,0.007598481,0.00191969,0.0009967923,0.004532698,0.8322348,0.002681751,0.1484871],"genre_scores_gemma":[0.008045834,0.00140759,0.03904059,0.0009484151,0.0003428647,0.0183421,0.3637322,0.003303944,0.5648365],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8241915,"threshold_uncertainty_score":0.8335142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1712004122368861,"score_gpt":0.3736179113520849,"score_spread":0.2024174991151988,"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."}}