{"id":"W2790288482","doi":"10.1093/imaman/dpy002","title":"The alpha male genetic algorithm","year":2018,"lang":"en","type":"article","venue":"IMA Journal of Management Mathematics","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Alpha (finance); Computer science; Algorithm; Mathematics; Statistics","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":[0.001157152,0.0007268279,0.0006715572,0.000985502,0.0007200601,0.001131774,0.001565289,0.001178121,0.004759094],"category_scores_gemma":[0.002907013,0.0002953522,0.0006374053,0.001032123,0.0007809324,0.0008207486,0.0009641483,0.001046678,0.001517905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006903553,"about_ca_system_score_gemma":0.001244709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001691451,"about_ca_topic_score_gemma":0.001422222,"domain_scores_codex":[0.999198,0.0003175607,0.00002824553,0.0001146849,0.0002403055,0.0001012503],"domain_scores_gemma":[0.9992344,0.0003167997,0.00008629873,0.0001113057,0.0001929625,0.00005828159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001696091,0.0001681719,0.002609116,0.0001952561,0.0001301945,0.0002544685,0.0002365302,0.4474693,0.004276979,0.1292851,0.01276111,0.4024442],"study_design_scores_gemma":[0.00007856973,0.0001767131,0.0005366037,0.00006563069,0.0000563836,0.000312762,0.00005443291,0.9137802,0.003292566,0.04830033,0.03331784,0.00002803933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01597099,0.0006495321,0.9578784,0.0003515623,0.0001816912,0.0001406364,0.00009754552,0.0006588969,0.02407084],"genre_scores_gemma":[0.3102333,0.001073236,0.6574818,0.0005274558,0.0002006119,0.0004625505,0.0003577431,0.0002085626,0.02945491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004759094,"threshold_uncertainty_score":0.01592076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650732607309121,"score_gpt":0.2827583594331851,"score_spread":0.2662510333600939,"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."}}