{"id":"W2748749446","doi":"10.1093/bjps/axx041","title":"Beyond ‘Interaction’: How to Understand Social Effects on Social Cognition","year":2017,"lang":"en","type":"article","venue":"The British Journal for the Philosophy of Science","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Interactivity; Cognition; Perspective (graphical); Social relation; Cognitive science; Confusion; Social cognition; Psychology; Computer science; Cognitive psychology; Epistemology; Social psychology; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001276041,0.00008668994,0.0001320069,0.00005067525,0.01356246,0.001024038,0.0008760051,0.00003185595,0.00003160771],"category_scores_gemma":[0.0003095583,0.00006255029,0.0001252334,0.00009554689,0.001017295,0.0002063224,0.00007796178,0.0003335359,0.00002195392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006034491,"about_ca_system_score_gemma":0.00004964948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000161753,"about_ca_topic_score_gemma":0.000007666146,"domain_scores_codex":[0.9989438,0.00005876616,0.0001359511,0.0001903805,0.0004059244,0.0002651495],"domain_scores_gemma":[0.9991084,0.0002486668,0.0002916959,0.0001300277,0.0001579693,0.00006318519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001650191,0.000405595,0.00009934849,0.00005628358,0.0003705336,0.00008217718,0.02520967,0.00001434394,0.01134839,0.191857,0.07895342,0.6899531],"study_design_scores_gemma":[0.003715152,0.001338424,0.5011853,0.0007712184,0.0002013521,0.001553918,0.00684312,0.00002842117,0.002807512,0.4715917,0.009398256,0.0005656847],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7623355,0.0001734537,0.0006340192,0.1727871,0.005432671,0.0007152846,0.00004464329,0.00002465026,0.05785264],"genre_scores_gemma":[0.996501,0.00001210304,0.00004674111,0.000877919,0.002007771,0.000007462281,5.267965e-7,0.000009570204,0.0005368752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6893874,"threshold_uncertainty_score":0.9877217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07462284184558464,"score_gpt":0.3547775337677107,"score_spread":0.280154691922126,"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."}}