{"id":"W2130962282","doi":"10.1002/bdm.1904","title":"Inferring Others' Hidden Thoughts: Smart Guesses in a Low Diagnostic World","year":2015,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Deception detection and forensic psychology","field":"Psychology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of British Columbia","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Irish Research Council for the Humanities and Social Sciences","keywords":"Context (archaeology); Psychology; Value (mathematics); Social psychology; Confirmation bias; Cognitive psychology; Lie detection; Epistemology; Computer science; Philosophy; Deception","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":[0.00517634,0.0003815306,0.0004387251,0.0008274521,0.0005388441,0.002065815,0.0004795282,0.001111472,0.002790292],"category_scores_gemma":[0.07152654,0.0004952991,0.0002509443,0.0002982498,0.002197558,0.002973307,0.001701097,0.001402608,0.0003785433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003390943,"about_ca_system_score_gemma":0.0002074323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003961029,"about_ca_topic_score_gemma":0.0003570901,"domain_scores_codex":[0.9969194,0.001667601,0.0002318194,0.0003773111,0.0006213685,0.0001823835],"domain_scores_gemma":[0.9532139,0.03095758,0.008846016,0.00461846,0.001414112,0.0009499005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01004002,0.0007745482,0.5802402,0.0009100481,0.0006431906,0.003621819,0.05179165,0.009092271,0.1680706,0.02196902,0.002212276,0.1506343],"study_design_scores_gemma":[0.000451468,0.002453231,0.5992888,0.0006790671,0.0006379093,0.005918121,0.02219775,0.0974944,0.1044667,0.1608925,0.004993539,0.0005265415],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928066,0.00008302963,0.005415855,0.0002403888,0.00001167006,0.00001209143,0.00002835265,0.00003227954,0.001369729],"genre_scores_gemma":[0.9981599,0.00002620329,0.001637428,0.00005098611,0.000006556097,0.000003808669,0.00002592907,0.000006235007,0.00008295586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00517634,"threshold_uncertainty_score":0.0273754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0869167357280344,"score_gpt":0.4202337297077499,"score_spread":0.3333169939797155,"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."}}