{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0269345,0.001280964,0.002880739,0.002148921,0.001968417,0.00453274,0.003437256,0.004730288,0.004464068],"category_scores_gemma":[0.2736421,0.0009436817,0.001145435,0.001920461,0.003063753,0.00919883,0.002589018,0.007569091,0.001238856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001194323,"about_ca_system_score_gemma":0.001798634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003764673,"about_ca_topic_score_gemma":0.00443945,"domain_scores_codex":[0.9826386,0.008975325,0.0009693989,0.004153633,0.002511306,0.0007516165],"domain_scores_gemma":[0.7147349,0.2498359,0.008834225,0.01653749,0.006940437,0.003117058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005534103,0.0008570876,0.07571671,0.001027347,0.002193414,0.0009013512,0.001206315,0.2097638,0.003562164,0.1044947,0.03431304,0.5604301],"study_design_scores_gemma":[0.000370335,0.0005299191,0.009682062,0.0002155732,0.0004168516,0.0003577244,0.0003415318,0.6019791,0.004074217,0.3770209,0.004865592,0.0001462324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1972695,0.003420911,0.7788272,0.009549745,0.0008952642,0.0002108653,0.0008904351,0.00179459,0.007141505],"genre_scores_gemma":[0.9209253,0.0005821402,0.07412438,0.001467698,0.0005592412,0.00009826971,0.0007493658,0.0002525315,0.001241098],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0269345,"threshold_uncertainty_score":0.142445,"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."}}