{"id":"W3170236218","doi":"10.2139/ssrn.3806587","title":"The slicing method: determining insensitivity regions of probability weighting functions","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Slicing; Weighting; Computer science; Statistics; Mathematics; Econometrics; Computer graphics (images); Physics","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":[0.008723577,0.001587531,0.001620204,0.003660474,0.0009269212,0.001975374,0.002070111,0.001148684,0.005095415],"category_scores_gemma":[0.03941713,0.001693438,0.001734556,0.001906641,0.001614955,0.003218009,0.002172834,0.002305303,0.0006989664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009245732,"about_ca_system_score_gemma":0.002184881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004874749,"about_ca_topic_score_gemma":0.003503021,"domain_scores_codex":[0.9980384,0.0009904949,0.0001033988,0.0002664274,0.0004556599,0.0001456913],"domain_scores_gemma":[0.9762133,0.01979843,0.000800044,0.001534618,0.001257328,0.0003962651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006682444,0.0001348,0.005207358,0.0006744483,0.0003573629,0.0005463015,0.0009270583,0.3651312,0.01701501,0.2796704,0.006992376,0.3226754],"study_design_scores_gemma":[0.0000379074,0.0000527783,0.001059962,0.00007247776,0.00009572229,0.0001752766,0.00005585605,0.838446,0.007339304,0.1501094,0.002508673,0.00004670323],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005118174,0.0001203251,0.9936796,0.00002415996,0.000005444268,0.00002589588,0.00007247215,0.0002668209,0.0006869754],"genre_scores_gemma":[0.1446799,0.0003551819,0.8525295,0.00008431396,0.00003407869,0.0001999696,0.0004854386,0.0007317067,0.0008998375],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008723577,"threshold_uncertainty_score":0.04613519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02492038548163724,"score_gpt":0.2736906101696046,"score_spread":0.2487702246879674,"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."}}