{"id":"W4318696273","doi":"10.1007/s10530-023-03003-9","title":"Trait variation in a successful global invader: a large-scale analysis of morphological variance and integration in the brown trout","year":2023,"lang":"en","type":"article","venue":"Biological Invasions","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Institut Polaire Français Paul Emile Victor","keywords":"Biology; Brown trout; Salmo; Population; Ecology; Variation (astronomy); Trait; Genetic variation; Population size; Range (aeronautics); Trout; Phenotypic plasticity; Phenotypic trait; Selection (genetic algorithm); Adaptation (eye); Evolutionary biology; Phenotype; Demography; Fishery; Fish <Actinopterygii>","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003653988,0.00008639539,0.0001678561,0.00008820138,0.00005164571,0.00001440311,0.0001655412,0.0001992802,0.00005183452],"category_scores_gemma":[0.0002100387,0.00005518389,0.00006639489,0.001076223,0.00007370156,0.000004396695,0.00009268884,0.00008479582,0.000001872659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008104261,"about_ca_system_score_gemma":0.00001474986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001435624,"about_ca_topic_score_gemma":0.001749381,"domain_scores_codex":[0.9990637,0.0002305471,0.0002120464,0.0002578174,0.00008721145,0.0001487104],"domain_scores_gemma":[0.9996851,0.00005186397,0.00006274152,0.0001441429,0.00002696297,0.00002919927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001623566,0.0002295783,0.885971,0.000006285562,0.00007984901,0.00001801965,0.0008945048,0.001749087,0.1058612,0.003453138,0.0002780169,0.001296927],"study_design_scores_gemma":[0.0003416588,0.0001550555,0.996336,0.000004636542,0.00003756136,0.000004534081,0.0005650037,0.001052312,0.000140728,0.001052457,0.0002405592,0.00006951698],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969857,0.00005821421,0.001950306,0.0004490927,0.00002870866,0.0001484809,0.0001751767,0.000007473046,0.0001968273],"genre_scores_gemma":[0.9986387,0.0001231129,0.0004314075,0.0003083798,0.00001848706,0.00001368857,0.0004504981,0.000001362242,0.00001436621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.110365,"threshold_uncertainty_score":0.2250334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07631881487860422,"score_gpt":0.2759711886958054,"score_spread":0.1996523738172012,"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."}}