{"id":"W4214653409","doi":"10.1111/mec.16415","title":"Combining population genomics with demographic analyses highlights habitat patchiness and larval dispersal as determinants of connectivity in coastal fish species","year":2022,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Nærings- og Fiskeridepartementet; Norges Forskningsråd","keywords":"Biological dispersal; Biology; Habitat; Ecology; Population genomics; Population; Larva; Ichthyoplankton; Fish <Actinopterygii>; Genomics; Fishery; Genome; Genetics","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":[0.000739592,0.000188821,0.0002361306,0.001037281,0.0002739919,0.0004320976,0.0002475355,0.0002541191,0.0005731059],"category_scores_gemma":[0.0009575579,0.0001688093,0.0003826353,0.0007642811,0.0003512737,0.000568477,0.0005776985,0.0004065993,0.00007732582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003204883,"about_ca_system_score_gemma":0.000226867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005460592,"about_ca_topic_score_gemma":0.01347149,"domain_scores_codex":[0.9997225,0.000071664,0.00001770548,0.0001325242,0.00002498565,0.000030423],"domain_scores_gemma":[0.9994634,0.0002195334,0.0001479872,0.00005128111,0.00005557033,0.00006234638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000090908,0.00006862757,0.9082717,0.00007536718,0.000395074,0.0001394519,0.001037861,0.002628766,0.06022784,0.000865243,0.0001572559,0.02604196],"study_design_scores_gemma":[0.000002753165,0.00003175261,0.9951461,0.00000586495,0.00003901197,0.0000532839,0.0002437112,0.003514912,0.0003192844,0.000397039,0.0002380822,0.000008275008],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969636,0.00008456819,0.002415181,0.00003471112,0.000001769712,0.000003168267,0.0001447613,0.00001279974,0.0003393707],"genre_scores_gemma":[0.9975548,0.00004776657,0.002077885,0.0000282416,0.000003419482,0.000007316032,0.0001857472,0.000005785107,0.00008907992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005460592,"threshold_uncertainty_score":0.01085764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01049708269537523,"score_gpt":0.2424566134047972,"score_spread":0.231959530709422,"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."}}