{"id":"W3186604173","doi":"","title":"Children's Use of Causal Structure When Making Similarity Judgments","year":2021,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Jacobs Foundation","keywords":"Similarity (geometry); Causal reasoning; Psychology; Causal structure; Narrative; Causation; Causal inference; Metric (unit); Causal chain; Causality (physics); Causal analysis; Causal model; Cognitive psychology; Contrast (vision); Cognition; Epistemology; Artificial intelligence; Computer science; Linguistics; Mathematics; Econometrics; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002320912,0.0003524453,0.0003001539,0.000966448,0.0002105052,0.002100307,0.0004167276,0.0007396152,0.002678703],"category_scores_gemma":[0.01076111,0.0004276367,0.0003571393,0.0002216409,0.001101114,0.00197377,0.0009597327,0.0009772503,0.0005837317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003079333,"about_ca_system_score_gemma":0.0003885097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003338024,"about_ca_topic_score_gemma":0.004405957,"domain_scores_codex":[0.9990935,0.000157805,0.00008901116,0.0001906811,0.0003058342,0.0001631867],"domain_scores_gemma":[0.9934391,0.003151415,0.001597732,0.0006161016,0.0008046997,0.00039092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005945207,0.0003880224,0.580409,0.000503748,0.0001447526,0.003605388,0.08675311,0.001653285,0.2051558,0.00617126,0.001833301,0.1127877],"study_design_scores_gemma":[0.00004493421,0.001098757,0.9029398,0.0002775045,0.0001948305,0.002501008,0.02227867,0.003557282,0.05066576,0.005885304,0.01036922,0.0001869486],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966246,0.0001284808,0.0007881828,0.00005309246,0.000007627852,0.00001062274,0.00006728896,0.00003793728,0.002282145],"genre_scores_gemma":[0.9964679,0.0002099968,0.002148459,0.00003441927,0.000003279201,0.00001570181,0.0001568723,0.00001144041,0.0009518124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003338024,"threshold_uncertainty_score":0.01227432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02480090741379541,"score_gpt":0.2466960638740723,"score_spread":0.2218951564602769,"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."}}