{"id":"W2562667406","doi":"10.1038/srep39451","title":"Difference in evolutionary patterns of strongly or weakly selected characters among ant populations","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics","keywords":"Gene flow; Biology; Evolutionary biology; Selection (genetic algorithm); Stabilizing selection; Character (mathematics); Divergence (linguistics); Population; Directional selection; Genetic variation; Mechanism (biology); ANT; Gene; Genetics; Ecology; Demography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.000386176,0.0001433614,0.0002588562,0.001260764,0.0004707972,0.0005860556,0.0002525219,0.000391713,0.0007676223],"category_scores_gemma":[0.00129811,0.0001460421,0.0002499619,0.0004939663,0.0005911652,0.0002630461,0.000495044,0.0003566335,0.0001747475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001912585,"about_ca_system_score_gemma":0.0001424577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003597451,"about_ca_topic_score_gemma":0.001022562,"domain_scores_codex":[0.999621,0.00008893797,0.00003999073,0.0001448896,0.00005850165,0.0000465424],"domain_scores_gemma":[0.9991122,0.0002692876,0.0002149728,0.0001212214,0.0001505076,0.0001317236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009207229,0.0001655236,0.6310003,0.0001053287,0.0003673794,0.00027889,0.002888476,0.001023507,0.3359277,0.000942631,0.0001134864,0.02626595],"study_design_scores_gemma":[0.000008400166,0.0001386568,0.9956158,0.000005995787,0.00004101748,0.0003270337,0.0003465849,0.0008401465,0.002055713,0.0002951091,0.0003118924,0.00001356931],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994695,0.00006053133,0.0001326511,0.000005516602,9.061067e-7,0.000002037127,0.00002000913,0.00000350874,0.0003054225],"genre_scores_gemma":[0.9994619,0.00003231369,0.0002368278,0.000007300996,0.000002449855,0.000004928055,0.00008494075,0.000003804708,0.0001654075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001260764,"threshold_uncertainty_score":0.002567947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04795028853930777,"score_gpt":0.2219943744425985,"score_spread":0.1740440859032907,"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."}}