{"id":"W2511227404","doi":"10.1371/journal.pgen.1006240","title":"On the Trail of Linked Selection","year":2016,"lang":"en","type":"letter","venue":"PLoS Genetics","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Biology; Selection (genetic algorithm); Computational biology; Evolutionary biology; Genetics; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007442622,0.0005553614,0.0009785473,0.0005907892,0.00273939,0.003896893,0.001596896,0.017875,0.008585314],"category_scores_gemma":[0.03391935,0.0004424262,0.0007202101,0.0004294127,0.01000194,0.006392953,0.003046905,0.0394268,0.005975519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002236234,"about_ca_system_score_gemma":0.001397544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001366435,"about_ca_topic_score_gemma":0.002090188,"domain_scores_codex":[0.9967775,0.001238749,0.0002075472,0.0007602361,0.0007539121,0.000261986],"domain_scores_gemma":[0.9794713,0.01424485,0.0008952736,0.002033505,0.001917498,0.001437603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003358194,0.00004412173,0.002031472,0.0001235003,0.00008289758,0.002315071,0.0004922192,0.0002870781,0.001066908,0.09948706,0.7989644,0.09476951],"study_design_scores_gemma":[0.0002050062,0.0001042922,0.001873224,0.0003189212,0.00003801471,0.001965163,0.0004036606,0.0008214189,0.0006456319,0.2294828,0.7640759,0.00006598388],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.001497271,0.004070038,0.001308473,0.9696191,0.0174071,0.00000742958,0.00005616708,0.00006901801,0.005965485],"genre_scores_gemma":[0.02556371,0.003917119,0.001089622,0.9119048,0.04774616,0.00003652166,0.00005021839,0.00006757236,0.009624137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.017875,"threshold_uncertainty_score":0.03936082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01462673131754939,"score_gpt":0.2243910549183134,"score_spread":0.209764323600764,"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."}}