{"id":"W2138556501","doi":"10.1007/978-3-540-24855-2_75","title":"On Naïve Crossover Biases with Reproduction for Simple Solutions to Classification Problems","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Crossover; Computer science; Simple (philosophy); Reproduction; Artificial intelligence; Algorithm; Biology; Philosophy; Epistemology; Genetics","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":[0.007748058,0.0006723448,0.001299419,0.001181652,0.0006460457,0.001828626,0.00242758,0.002082488,0.008619223],"category_scores_gemma":[0.05390392,0.0004843959,0.001083319,0.001355232,0.002539488,0.00365088,0.002437032,0.002831339,0.0005864414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001078,"about_ca_system_score_gemma":0.0005868854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009242742,"about_ca_topic_score_gemma":0.0009406467,"domain_scores_codex":[0.9972458,0.001588019,0.0001102281,0.0003534466,0.0005465737,0.0001558962],"domain_scores_gemma":[0.9668599,0.02851331,0.0006730212,0.002795633,0.0008312874,0.000326887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004421098,0.0001905071,0.002517235,0.0004432389,0.0001264662,0.0002510812,0.00053184,0.1399111,0.004175788,0.448449,0.007463798,0.3954978],"study_design_scores_gemma":[0.0001950352,0.000141547,0.0008757082,0.00009099324,0.00005852601,0.0002160896,0.00004743895,0.4028963,0.001322776,0.5913431,0.002777917,0.00003445059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08032225,0.001895947,0.8948755,0.001166752,0.000256708,0.0002197164,0.0001242236,0.0006763989,0.0204625],"genre_scores_gemma":[0.6142203,0.0009387035,0.3691821,0.0007520689,0.0004792151,0.0003663258,0.0002473799,0.0004212788,0.01339276],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008619223,"threshold_uncertainty_score":0.04097611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2484564080262124,"score_gpt":0.4061652919485467,"score_spread":0.1577088839223343,"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."}}