{"id":"W4244688954","doi":"10.31234/osf.io/vezg7","title":"Maximizing prediction","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Social and Intergroup Psychology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Variance (accounting); Demographics; Ingroups and outgroups; Race (biology); Population; Econometrics; Psychology; Social psychology; Mathematics; Demography; Sociology; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.006398396,0.001705716,0.001702564,0.001282811,0.0006756271,0.002134183,0.002151001,0.001709091,0.0102799],"category_scores_gemma":[0.02467929,0.0004987274,0.0008743927,0.001526371,0.0009949869,0.002614331,0.001778885,0.001846341,0.003112495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001325589,"about_ca_system_score_gemma":0.001993298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003459348,"about_ca_topic_score_gemma":0.003893352,"domain_scores_codex":[0.9965253,0.001600723,0.0001350803,0.00102601,0.0004182183,0.000294532],"domain_scores_gemma":[0.9890275,0.008096781,0.0005245753,0.001328771,0.0007485436,0.0002738728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004385397,0.0003251105,0.03276284,0.0005342995,0.0004233941,0.0003311087,0.0003872574,0.3662405,0.001155199,0.1293292,0.03865881,0.4294137],"study_design_scores_gemma":[0.00006562842,0.0001288718,0.004904933,0.0001088574,0.00008048044,0.0001538454,0.0001172603,0.7657274,0.0009968178,0.2192923,0.00838615,0.00003750044],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1084361,0.00292661,0.8203375,0.0079414,0.0005310685,0.0005949257,0.004144283,0.001705174,0.05338296],"genre_scores_gemma":[0.8574136,0.001097663,0.1212237,0.001052285,0.0005565094,0.0005916988,0.002786461,0.0002795976,0.01499842],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0102799,"threshold_uncertainty_score":0.03438967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1111697770073748,"score_gpt":0.3828217547806529,"score_spread":0.2716519777732781,"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."}}