{"id":"W2315748902","doi":"10.1111/mec.13577","title":"History repeats itself: genomic divergence in copepods","year":2016,"lang":"en","type":"letter","venue":"Molecular Ecology","topic":"Marine Biology and Ecology Research","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université de Montréal","funders":"","keywords":"Biology; Evolutionary biology; Divergence (linguistics); Natural selection; Population; Scale (ratio); Selection (genetic algorithm); Evolutionary ecology; Ecology; Genealogy; History; Demography; Computer science; Artificial intelligence; Geography","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":[0.003692293,0.0003458242,0.0005319295,0.0003486003,0.001602686,0.002099053,0.001246541,0.01633774,0.003015868],"category_scores_gemma":[0.01873382,0.0004162827,0.0004991728,0.0004519125,0.004753792,0.00315275,0.001617673,0.01556234,0.003027692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001455455,"about_ca_system_score_gemma":0.0008813462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00254595,"about_ca_topic_score_gemma":0.003574459,"domain_scores_codex":[0.9979661,0.0006860244,0.0001731994,0.0004732654,0.0005528953,0.0001486894],"domain_scores_gemma":[0.9887561,0.007714809,0.0008408057,0.001008767,0.0009347405,0.0007448298],"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":[0.0003273938,0.00004585633,0.007311933,0.0001722134,0.00008646173,0.002877712,0.001068659,0.0002520259,0.001432106,0.01129567,0.880889,0.09424089],"study_design_scores_gemma":[0.0001993293,0.0001187594,0.01806573,0.0005321463,0.00007140833,0.006091858,0.001130196,0.0007206877,0.001623482,0.07044297,0.9008551,0.0001482344],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.003348283,0.00788776,0.0004964466,0.9685204,0.01609325,0.000005060151,0.00007735543,0.00004072642,0.003530667],"genre_scores_gemma":[0.04095941,0.007886457,0.0004752993,0.8766396,0.06577803,0.00002628647,0.00007859703,0.0000499275,0.008106396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01633774,"threshold_uncertainty_score":0.01952696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01712644823951717,"score_gpt":0.2151278020235073,"score_spread":0.1980013537839901,"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."}}