{"id":"W2272068344","doi":"10.1016/j.cognition.2015.12.008","title":"Perspective-taking behavior as the probabilistic weighing of multiple domains","year":2016,"lang":"en","type":"article","venue":"Cognition","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":89,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nuance Communications (Canada); University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Perspective (graphical); Cognitive psychology; Common ground; Point (geometry); Probabilistic logic; Process (computing); Perspective-taking; Bayesian probability; Cognitive science; Test (biology); Resolution (logic); Artificial intelligence; Social psychology; Computer science; Mathematics","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":[0.000215453,0.00006582854,0.00007856816,0.00004329082,0.0000995062,0.00003962963,0.0002668497,0.00003206662,0.00001712997],"category_scores_gemma":[0.0006137571,0.00003669842,0.00004879467,0.0001370473,0.00006752982,0.0002328836,0.00006357013,0.00003838724,0.00009227126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005713448,"about_ca_system_score_gemma":0.00004349567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000608138,"about_ca_topic_score_gemma":0.00003551807,"domain_scores_codex":[0.9992915,0.00007079876,0.0001344268,0.0001890563,0.0001779352,0.0001362456],"domain_scores_gemma":[0.9991307,0.0002675168,0.0001356754,0.0002474012,0.0001850126,0.00003375613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001000877,0.0006113307,0.01182221,0.0000811436,0.00007215654,0.00006755139,0.01094867,0.000006118768,0.4317071,0.3543267,0.0004532269,0.1898038],"study_design_scores_gemma":[0.00688752,0.001030372,0.206534,0.001329867,0.0002231271,0.0002937773,0.003204959,0.00327216,0.3501523,0.4242503,0.001645571,0.001176112],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7447816,0.0001165037,0.2363733,0.000886659,0.0009061857,0.0007776849,0.0000146613,0.0001784155,0.01596503],"genre_scores_gemma":[0.9986821,0.000002417667,0.001046956,0.00004590975,0.0001052601,0.00006162097,0.000001187551,0.000004672635,0.00004991355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2539005,"threshold_uncertainty_score":0.1496518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02794349954596962,"score_gpt":0.2696712362820068,"score_spread":0.2417277367360372,"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."}}