{"id":"W2565667022","doi":"10.1037/dec0000073","title":"Rejecting outliers: Surprising changes do not always improve belief updating.","year":2016,"lang":"en","type":"article","venue":"Decision","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Outlier; Computer science; Psychology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009963179,0.0001818692,0.0001960069,0.0001454526,0.0002399792,0.0003325577,0.000854308,0.0001146429,0.00001898022],"category_scores_gemma":[0.000525945,0.000123127,0.00006232262,0.0002845905,0.00003347318,0.0005081188,0.0004600262,0.0001450041,0.000233467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006568803,"about_ca_system_score_gemma":0.00005065069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003282935,"about_ca_topic_score_gemma":0.0000162686,"domain_scores_codex":[0.9981101,0.00006083309,0.0002994785,0.0006553184,0.0004627874,0.0004115256],"domain_scores_gemma":[0.9981737,0.0005702477,0.0001531715,0.0008041708,0.000164269,0.0001344504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001043318,0.00001686697,0.00009244128,0.000002742529,0.000004418253,0.000008698109,0.0004303798,0.000007295785,0.0252649,0.008218009,0.0005211385,0.9654227],"study_design_scores_gemma":[0.005920305,0.002195689,0.006096662,0.004497855,0.00006678871,0.0002445862,0.001066,0.1666542,0.4878176,0.2805205,0.04039913,0.004520759],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07516848,0.0000944375,0.920525,0.001251053,0.0008431844,0.0000883321,0.000003744006,0.0002470732,0.001778706],"genre_scores_gemma":[0.8971835,0.00005423934,0.101931,0.0004536088,0.0001807108,0.000006579294,5.823705e-7,0.00001558261,0.0001742159],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9609019,"threshold_uncertainty_score":0.5020974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02868503939165357,"score_gpt":0.2753483400176532,"score_spread":0.2466633006259996,"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."}}