{"id":"W2396739398","doi":"","title":"Children's Causal Learning from Fiction: Assessing the Proximity Between Real and Fictional Worlds","year":2012,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Fictional universe; Generalization; Possible world; Space (punctuation); Causal structure; Psychology; Order (exchange); Cognitive psychology; Epistemology; Computer science; Literature; Art; Philosophy; Narrative","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":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000348444,0.0003069722,0.0002600915,0.00009325644,0.000649373,0.001241748,0.0002517908,0.0001886673,0.001219863],"category_scores_gemma":[0.0001174159,0.0002348198,0.0001096088,0.0002864304,0.0001465046,0.002953979,0.0002574735,0.001197489,0.001008541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003532679,"about_ca_system_score_gemma":0.00005209158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002207042,"about_ca_topic_score_gemma":4.417936e-7,"domain_scores_codex":[0.9979489,0.0002617713,0.0003863021,0.0004833269,0.0003359826,0.0005836539],"domain_scores_gemma":[0.9988068,0.0004379205,0.0001737132,0.0002540061,0.00001960792,0.000307967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003219847,0.00009489075,0.9853163,0.000003377807,0.0001297619,0.000004018411,0.0002786691,0.00000161568,0.00001264068,0.00180792,0.002391874,0.009926728],"study_design_scores_gemma":[0.0003194918,0.00003472121,0.8678294,0.00003398531,0.00003185124,0.00001932773,0.0001518016,0.000003734295,0.00003484523,0.0004174353,0.130851,0.000272325],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9511369,0.0003820379,0.0001163928,0.0008225381,0.0003385693,0.0002170119,0.0003905276,0.0003866963,0.04620932],"genre_scores_gemma":[0.9935104,0.00001154192,0.0003333303,0.0002295932,0.002461349,0.00002200706,0.00132253,0.00006836891,0.002040834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1284592,"threshold_uncertainty_score":0.9997951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02177371768271887,"score_gpt":0.2584935453927378,"score_spread":0.236719827710019,"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."}}