{"id":"W2015249681","doi":"10.3758/bf03193282","title":"Feature-feature causal relations and statistical co-occurrences in object concepts","year":2007,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Deafness and Other Communication Disorders; National Institute of Mental Health; National Institutes of Health","keywords":"Feature (linguistics); Psychology; Object (grammar); Cognitive psychology; Artificial intelligence; Pattern recognition (psychology); Natural language processing; Linguistics; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007346053,0.0006358211,0.001065504,0.004291932,0.001710377,0.004750249,0.002559384,0.002978414,0.006418762],"category_scores_gemma":[0.0666002,0.001608103,0.001947033,0.003796572,0.005418649,0.01503877,0.002593829,0.002858428,0.000490414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001494489,"about_ca_system_score_gemma":0.001323638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003828306,"about_ca_topic_score_gemma":0.003505402,"domain_scores_codex":[0.9953349,0.002241235,0.0003024063,0.00108172,0.0008075543,0.000232138],"domain_scores_gemma":[0.9407907,0.05047901,0.003475034,0.00297094,0.001684336,0.0006001203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004995501,0.0002107933,0.01428267,0.0003843071,0.000333865,0.0005357079,0.00253056,0.01465289,0.002395984,0.8874514,0.001421639,0.07530051],"study_design_scores_gemma":[0.00002284008,0.00001782309,0.003456237,0.00002984522,0.00006860188,0.0002396639,0.0001254385,0.02855166,0.0006015515,0.9662145,0.0006445236,0.00002726294],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2004196,0.002547659,0.7854862,0.002718663,0.0001207819,0.00009132031,0.0004079156,0.0003355065,0.007872446],"genre_scores_gemma":[0.9186557,0.001068606,0.07764822,0.0002340582,0.0002367815,0.0001883875,0.0004103769,0.00009908284,0.001458824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007346053,"threshold_uncertainty_score":0.03885007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02418926036873739,"score_gpt":0.3225691303155254,"score_spread":0.298379869946788,"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."}}