{"id":"W2540634505","doi":"10.33915/etd.6941","title":"Migratory Genomics of Lake Sturgeon","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Geological Survey; West Virginia University; Ontario Ministry of Natural Resources and Forestry; University of Windsor; National Institute of Food and Agriculture; Michigan Department of Natural Resources; Ministry of Natural Resources; U.S. Fish and Wildlife Service; U.S. Department of Agriculture","keywords":"Sturgeon; Lake sturgeon; Fishery; Geography; Habitat; Population; Bay; Ecology; Drainage basin; Range (aeronautics); Fish <Actinopterygii>; Acipenser; Biology; Cartography; Archaeology","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":[0.00008254193,0.0001267826,0.0001188297,0.0004308188,0.0002448446,0.00018636,0.00007252308,0.0001294205,0.001001451],"category_scores_gemma":[0.0001800701,0.00006674956,0.0001756541,0.0005106805,0.00008337725,0.00009650095,0.0001785893,0.0001376739,0.0001459598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002312777,"about_ca_system_score_gemma":0.0001215184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008831839,"about_ca_topic_score_gemma":0.01867698,"domain_scores_codex":[0.9999499,0.000005104675,0.000003114494,0.00002088022,0.00001046024,0.0000105406],"domain_scores_gemma":[0.9999063,0.00001099541,0.00003163983,0.000004109463,0.00002452047,0.00002238848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006705669,0.00006407393,0.4768454,0.0001360277,0.000116082,0.0002689911,0.002155684,0.000551176,0.4884824,0.0003196784,0.001083671,0.02930615],"study_design_scores_gemma":[0.000002385237,0.00006966026,0.9972637,0.000003941317,0.00001593573,0.0000702671,0.0001736409,0.0002303521,0.001348786,0.00002606499,0.0007917369,0.000003413568],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987827,0.00006979884,0.000115827,0.00001951537,0.000001864274,0.000002079558,0.0005318467,0.000005956967,0.0004702619],"genre_scores_gemma":[0.9951149,0.0001025853,0.0005480715,0.00007244448,0.000004667913,0.0000134931,0.00279305,0.00001058443,0.00134022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008831839,"threshold_uncertainty_score":0.01756084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004659971992785618,"score_gpt":0.2029992332529392,"score_spread":0.1983392612601536,"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."}}