{"id":"W2150665430","doi":"10.1111/j.1420-9101.2010.02188.x","title":"Haploids adapt faster than diploids across a range of environments","year":2010,"lang":"en","type":"article","venue":"Journal of Evolutionary Biology","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":133,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; FAS Center for Systems Biology, Harvard University; Killam Trusts; Universities Space Research Association","keywords":"Biology; Ploidy; Adaptation (eye); Selection (genetic algorithm); Doubled haploidy; Range (aeronautics); Population; Genetics; Local adaptation; Evolutionary biology; Gene; Machine learning","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":[0.0004497422,0.0002972412,0.0003216888,0.0003748188,0.0001710648,0.0003876159,0.0002288902,0.000349981,0.0008184832],"category_scores_gemma":[0.001401217,0.0002755309,0.000314411,0.0002291158,0.0003246097,0.0004626832,0.0005096692,0.0006257267,0.0002192894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003573792,"about_ca_system_score_gemma":0.0001340718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003654234,"about_ca_topic_score_gemma":0.000640853,"domain_scores_codex":[0.9997821,0.00003832013,0.00002071767,0.00008934892,0.00003955487,0.00002983521],"domain_scores_gemma":[0.9990362,0.0004045208,0.0002114508,0.0001873718,0.00007085449,0.0000897185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003389187,0.00006209304,0.05467602,0.000107571,0.0001773926,0.0002167084,0.0003357056,0.01046602,0.9166219,0.001126456,0.0001707667,0.01570053],"study_design_scores_gemma":[0.0001654905,0.001553156,0.602304,0.0000597075,0.0002980582,0.002864632,0.0009322294,0.04298433,0.3313511,0.009813358,0.007449813,0.0002240372],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984895,0.00007596728,0.001031722,0.0000217487,0.000002810196,0.000003313229,0.00003994767,0.00002924334,0.0003057904],"genre_scores_gemma":[0.9968624,0.0001391934,0.002323144,0.00004643079,0.000002581285,0.00001213146,0.0002007267,0.00003793027,0.0003755442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008184832,"threshold_uncertainty_score":0.002738118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006602528070234736,"score_gpt":0.261784291888212,"score_spread":0.2551817638179772,"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."}}