{"id":"W4410904239","doi":"10.1111/jfb.70093","title":"Low genetic variation and strong genetic structure across a range of geographical scales in European smelt (<scp><i>Osmerus eperlanus</i></scp> L.)","year":2025,"lang":"en","type":"article","venue":"Journal of Fish Biology","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centre d'étude de la biodiversité amazonienne; Eesti Maaülikool; Tartu Ülikool; Agence Nationale de la Recherche; Queen's University Belfast; Llywodraeth Cymru; Natural Resources Wales; Queen's University; Agentschap voor Natuur en Bos","keywords":"Biology; Smelt; Genetic variation; Isolation by distance; Range (aeronautics); Biological dispersal; Phylogeography; Population; Ecology; Microsatellite; Genetic structure; Zoology; Genetic diversity; Genetic variability; Evolutionary biology; Fishery; Phylogenetic tree; Genetics; Genotype; Demography; Fish <Actinopterygii>","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":[0.0002746588,0.0001209915,0.0001771534,0.0008420604,0.0003270133,0.000352852,0.0001538237,0.0002113605,0.0009870882],"category_scores_gemma":[0.0003251229,0.00007371039,0.0001680362,0.0004467065,0.0003690869,0.0001535193,0.0003938609,0.0001733039,0.0001210509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000224346,"about_ca_system_score_gemma":0.0001206663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003298931,"about_ca_topic_score_gemma":0.00897423,"domain_scores_codex":[0.9998591,0.00002930779,0.00001807604,0.00005025104,0.00002576091,0.00001749012],"domain_scores_gemma":[0.9996951,0.00006736553,0.000121693,0.00001640702,0.00004377635,0.00005573646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000447004,0.00007416699,0.8610624,0.00006178408,0.0001902227,0.0004827908,0.001258052,0.0004946765,0.1240721,0.0001447425,0.0001154082,0.01159671],"study_design_scores_gemma":[0.000004259431,0.00008777604,0.9981375,0.000006756089,0.00001337393,0.0001670096,0.000289319,0.0002897652,0.0008123111,0.00002348976,0.0001647919,0.000003565326],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997911,0.00001285839,0.00006516767,0.000005026763,4.122663e-7,5.759605e-7,0.00002594392,0.000001501067,0.00009763318],"genre_scores_gemma":[0.999661,0.000009707676,0.0001262952,0.000006644405,7.967611e-7,0.000001791147,0.00008656666,0.000001096014,0.0001061216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003298931,"threshold_uncertainty_score":0.006559491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004576073237447137,"score_gpt":0.2232841692457582,"score_spread":0.2187080960083111,"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."}}