{"id":"W2515482889","doi":"10.1002/jwmg.21131","title":"Environmental factors influence lesser scaup migration chronology and population monitoring","year":2016,"lang":"en","type":"article","venue":"Journal of Wildlife Management","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Wildlife Federation; Environment and Climate Change Canada; Birds Canada; Western University","funders":"U.S. Fish and Wildlife Service","keywords":"Aythya; Waterfowl; Anas; Population; Flyway; Habitat; Fishery; Ecology; Geography; Bay; Wetland; Environmental science; Biology; Archaeology; Demography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004386795,0.0002031265,0.00013309,0.0005033759,0.0001863078,0.0003648775,0.0001193763,0.00009802936,0.0009203035],"category_scores_gemma":[0.001599564,0.00009716783,0.00011553,0.0004181038,0.0001129536,0.000256916,0.0001754102,0.0001286548,0.000124145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001632275,"about_ca_system_score_gemma":0.0001301205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009245379,"about_ca_topic_score_gemma":0.04558909,"domain_scores_codex":[0.9997668,0.00007360963,0.00002301896,0.00006487452,0.0000423844,0.00002936196],"domain_scores_gemma":[0.9983035,0.0003159946,0.0009117841,0.00008273842,0.0002677002,0.0001182705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001336345,0.000005694735,0.9970112,0.000004630431,0.0000120348,0.00001430839,0.00004039337,0.00007575064,0.0008523565,0.000003652793,0.0000363476,0.001930282],"study_design_scores_gemma":[1.535986e-7,0.000006911986,0.9997637,0.000001179522,0.000002315013,0.00001057141,0.00003089933,0.00009216808,0.00005306884,0.000001402809,0.0000372603,3.911282e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992842,0.00004732562,0.0001480465,0.00000656293,0.000001586491,0.000003790574,0.0001502753,0.000005872771,0.0003525247],"genre_scores_gemma":[0.9993549,0.0000387266,0.0002630675,0.000005290207,0.000002722887,0.000004260696,0.000201381,0.000002566887,0.0001270229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009245379,"threshold_uncertainty_score":0.01838309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008230541302052403,"score_gpt":0.2208901805813203,"score_spread":0.212659639279268,"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."}}