{"id":"W4409376867","doi":"10.1080/23273798.2025.2489602","title":"Scalar inference is supported by Theory of Mind networks in adults and children","year":2025,"lang":"en","type":"article","venue":"Language Cognition and Neuroscience","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Neurosciences Foundation","keywords":"Inference; Theory of mind; Scalar (mathematics); Computer science; Psychology; Cognitive psychology; Cognitive science; Artificial intelligence; Natural language processing; Mathematics; Cognition; Neuroscience","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001486429,0.00006694913,0.0000894115,0.00007486351,0.00004316724,0.00001638195,0.00005995246,0.00003952946,0.0001490896],"category_scores_gemma":[0.00008593577,0.00006061834,0.00001012522,0.0002169536,0.000156245,0.00003970837,0.00004249463,0.0001080434,0.000002007517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001967492,"about_ca_system_score_gemma":0.0000103205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000186566,"about_ca_topic_score_gemma":0.000005805039,"domain_scores_codex":[0.9993672,0.00006078725,0.000121301,0.0002693947,0.00005764952,0.0001236597],"domain_scores_gemma":[0.9997706,0.00007305953,0.00003979148,0.00006928433,0.00001337018,0.00003388359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004619477,0.0004421289,0.5859896,0.00005478364,0.00001539588,0.00005213338,0.01509669,0.000002163691,0.1294383,0.003301643,0.001283048,0.2638622],"study_design_scores_gemma":[0.00066067,0.00006139092,0.992016,0.0001225606,0.000006417966,0.000008571921,0.0003799308,0.0001091024,0.006330997,0.00009848193,0.0001252548,0.00008060155],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996201,0.0006247531,0.0003080085,0.0001245773,0.0000709587,0.0001059511,0.00001906783,0.000009910252,0.002535814],"genre_scores_gemma":[0.9977031,0.000102157,0.00001518327,0.001585019,0.000005623018,0.000003943104,0.00001058457,0.000002604824,0.0005718195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4060264,"threshold_uncertainty_score":0.2471944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007903862643224747,"score_gpt":0.2793240494637965,"score_spread":0.2714201868205717,"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."}}