{"id":"W3030881299","doi":"10.2139/ssrn.3374514","title":"Double Decoys and a Possible Parameterization: Empirical Analyses of Pairwise Normalization","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Pairwise comparison; Normalization (sociology); Econometrics; Mathematics; Statistics; Psychology; Computer science; Sociology; Social science","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":[0.01149019,0.001021993,0.001826564,0.001771133,0.002000346,0.002599081,0.004016244,0.001677489,0.01647625],"category_scores_gemma":[0.1034051,0.0006735175,0.001141596,0.002584235,0.005146435,0.01177296,0.003688478,0.00432939,0.00157558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001286141,"about_ca_system_score_gemma":0.001313087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001326173,"about_ca_topic_score_gemma":0.00155518,"domain_scores_codex":[0.9927607,0.003048793,0.0003852408,0.002004587,0.001178642,0.0006221955],"domain_scores_gemma":[0.9407413,0.029032,0.002629897,0.02404023,0.002440661,0.001115977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001208653,0.0007587721,0.02843575,0.0006902833,0.0004922834,0.0004292059,0.002177766,0.03338382,0.03378842,0.7551011,0.01240332,0.1311307],"study_design_scores_gemma":[0.00008518153,0.00019111,0.02517719,0.0001216129,0.000130608,0.0008223682,0.0005437246,0.209759,0.0175026,0.7404951,0.004889965,0.0002815024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5339527,0.0008552762,0.43715,0.001400697,0.0002048558,0.0001832708,0.0008925247,0.003115121,0.02224563],"genre_scores_gemma":[0.9708171,0.0001163781,0.02491912,0.0001897111,0.00003927793,0.0001397558,0.0007161062,0.001345634,0.00171695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01647625,"threshold_uncertainty_score":0.06076664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08520071835306386,"score_gpt":0.3843489063455589,"score_spread":0.299148187992495,"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."}}