{"id":"W2176102073","doi":"10.1139/f2012-073","title":"Small-scale dispersal and population structure in stream-living brown trout (<i>Salmo trutta</i>) inferred by mark–recapture, pedigree reconstruction, and population genetics","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Norges Forskningsråd","keywords":"Salmo; Brown trout; Biological dispersal; Biology; Mark and recapture; Philopatry; Juvenile; Population; Ecology; Genetic structure; Habitat; Trout; Isolation by distance; Salmonidae; Juvenile fish; Fishery; Zoology; Fish <Actinopterygii>; Genetic variation; Demography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0006097366,0.0001301524,0.000113802,0.0006628576,0.000218687,0.0002430676,0.0001982362,0.000118597,0.0003854407],"category_scores_gemma":[0.001105673,0.0001603985,0.0001776337,0.0003497444,0.0003692056,0.0003030751,0.0002470345,0.0001685254,0.00006902804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003852838,"about_ca_system_score_gemma":0.0002482781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01473901,"about_ca_topic_score_gemma":0.04038084,"domain_scores_codex":[0.999873,0.00004245328,0.00001146423,0.00004173822,0.00001685107,0.00001448938],"domain_scores_gemma":[0.9992138,0.000207684,0.0003901113,0.00004799366,0.00006079089,0.00007967695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000930028,0.00004120312,0.9809368,0.00001362568,0.00008402238,0.00007367468,0.0002582849,0.001293409,0.01102431,0.000100093,0.00006481072,0.006016675],"study_design_scores_gemma":[0.000005436539,0.00004029355,0.9964244,0.000002252552,0.00001762516,0.00005227658,0.0000765634,0.003063028,0.0002267759,0.00005520322,0.00003220648,0.00000392234],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998189,0.00001340478,0.0001306432,0.000003366879,2.676068e-7,6.45604e-7,0.000009636592,0.000001478242,0.00002169681],"genre_scores_gemma":[0.9995658,0.00001824341,0.0002998432,0.000003332753,0.000001871415,0.000002069012,0.00006880431,0.000001535918,0.00003848908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01473901,"threshold_uncertainty_score":0.02930641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01103595231635733,"score_gpt":0.1951687481740637,"score_spread":0.1841327958577063,"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."}}