{"id":"W3157090845","doi":"10.1111/faf.12565","title":"Continental‐scale acoustic telemetry and network analysis reveal new insights into stock structure","year":2021,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Ichthyology and Marine Biology","field":"Environmental Science","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Threatened species; Stock (firearms); Telemetry; Population; Fish stock; Fishery; Geography; Ecology; Computer science; Biology; Telecommunications; Fish <Actinopterygii>; Habitat","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":[0.0006429109,0.0001648453,0.000143962,0.001657671,0.000167941,0.0005664849,0.0002493038,0.0001635969,0.00119639],"category_scores_gemma":[0.001433047,0.0001000298,0.0001398386,0.001249556,0.0002685256,0.0007792287,0.000574454,0.0001939223,0.0001511491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002501219,"about_ca_system_score_gemma":0.0001484787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006176152,"about_ca_topic_score_gemma":0.01445971,"domain_scores_codex":[0.9998449,0.00005586584,0.00001378647,0.00004530984,0.00002183967,0.0000181946],"domain_scores_gemma":[0.9989567,0.0003600974,0.0003416996,0.0001123909,0.000161993,0.00006717225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004565959,0.0000161705,0.9594895,0.00003719388,0.0001822997,0.00006764023,0.0005746615,0.003828119,0.009995696,0.0007320261,0.0001548718,0.02487629],"study_design_scores_gemma":[0.000001556749,0.00002209968,0.9885951,0.00001578602,0.00004543563,0.00005483637,0.0006089171,0.008853446,0.0006113889,0.0006226661,0.0005627853,0.000006013141],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942159,0.0001264846,0.003934041,0.00003907868,0.000002640294,0.00000603465,0.0002408749,0.00001119685,0.001423885],"genre_scores_gemma":[0.9973357,0.00007734216,0.002109927,0.00001317283,0.000003308483,0.000004807304,0.0002144917,0.000003414889,0.0002377948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006176152,"threshold_uncertainty_score":0.0122804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004105086336649553,"score_gpt":0.1902644493319737,"score_spread":0.1861593629953241,"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."}}