{"id":"W2122427912","doi":"10.1023/b:mind.0000045987.92742.71","title":"Inductive Reasoning and Chance Discovery","year":2004,"lang":"en","type":"article","venue":"Minds and Machines","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Surprise; Computer science; Inductive reasoning; Psychology of reasoning; Bayesian probability; Artificial intelligence; Theory of computation; Dilemma; Planner; Machine learning; Model-based reasoning; Epistemology; Psychology; Algorithm; Knowledge representation and reasoning; Philosophy","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":[0.009940317,0.0007996301,0.001646906,0.003843059,0.002216419,0.004358933,0.002750044,0.002534524,0.008696195],"category_scores_gemma":[0.04508743,0.0008474846,0.002055323,0.003351704,0.009169532,0.01098632,0.004366717,0.004683654,0.0008938144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002130912,"about_ca_system_score_gemma":0.00128953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001382892,"about_ca_topic_score_gemma":0.00121226,"domain_scores_codex":[0.9920272,0.004686826,0.0003344067,0.001083216,0.001498188,0.0003700966],"domain_scores_gemma":[0.9381974,0.05542695,0.00182977,0.002512736,0.001406062,0.0006271214],"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":[0.00001404553,0.000007764732,0.0002968845,0.00003799523,0.00003120164,0.00004053314,0.0001204782,0.001503148,0.00003025768,0.9910625,0.0009192125,0.00593598],"study_design_scores_gemma":[0.000002788842,9.709054e-7,0.00003624834,0.000005211367,0.000003989644,0.00001399074,0.000009488845,0.001967109,0.00002588236,0.9973474,0.0005850392,0.000001939602],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03194647,0.006263086,0.8764169,0.02160181,0.0004371742,0.00007234697,0.0003075823,0.0002502376,0.06270443],"genre_scores_gemma":[0.8248872,0.004237128,0.147744,0.001886759,0.002442708,0.0003552157,0.0005465047,0.0001426165,0.01775785],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009940317,"threshold_uncertainty_score":0.05257004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005800492898316891,"score_gpt":0.2502030910019747,"score_spread":0.2444025981036579,"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."}}