{"id":"W1552983290","doi":"10.3968/5487","title":"Some Genetic Features of Population Migration","year":2014,"lang":"en","type":"article","venue":"Advances in natural science/Advances in natural sciences","topic":"Agriculture and Biological Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inbreeding; Population; Panmixia; Selection (genetic algorithm); Biology; Allele frequency; Natural selection; Genetics; Allele; Computer science; Demography; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002209495,0.0001675506,0.0002290616,0.0006368363,0.0003388247,0.0005628926,0.0003587573,0.0003427062,0.002342678],"category_scores_gemma":[0.001190373,0.000113273,0.0004227647,0.0007013401,0.0004615478,0.0005492362,0.000242047,0.0005285197,0.000302741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006757839,"about_ca_system_score_gemma":0.0004346755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004101123,"about_ca_topic_score_gemma":0.002170397,"domain_scores_codex":[0.9999011,0.00002024245,0.000006309373,0.00003384336,0.00002608213,0.00001244952],"domain_scores_gemma":[0.9998166,0.00004683186,0.00004624336,0.00001610902,0.00005841262,0.00001586384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0000322367,0.00003843076,0.03207168,0.0001424446,0.00006062179,0.0009366077,0.0006858762,0.06331546,0.009779875,0.8268377,0.005177028,0.06092206],"study_design_scores_gemma":[0.00003016137,0.00009022299,0.07711519,0.0000695728,0.00007089347,0.002679607,0.0003901763,0.2954881,0.001404265,0.5879709,0.03459276,0.00009810186],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4651873,0.004879249,0.4475917,0.002940824,0.000368069,0.0001161517,0.001490522,0.0003185667,0.07710756],"genre_scores_gemma":[0.9635071,0.001298759,0.01759777,0.0001285322,0.000188971,0.00006013106,0.0004403514,0.00005375535,0.01672462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004101123,"threshold_uncertainty_score":0.008154511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007180829506538582,"score_gpt":0.2597145680372807,"score_spread":0.2525337385307421,"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."}}