{"id":"W2995831818","doi":"10.1002/jwmg.21807","title":"A Meta‐Analysis of Band Reporting Probabilities for North American Waterfowl","year":2019,"lang":"en","type":"article","venue":"Journal of Wildlife Management","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome Prairie; Environment and Climate Change Canada","funders":"","keywords":"Waterfowl; Anas; Aythya; Population; Geography; Statistics; Econometrics; Demography; Mathematics; Ecology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008973407,0.00009738548,0.0006560293,0.0001387328,0.00003992987,0.00001012034,0.0001946441,0.00001645274,0.0007183864],"category_scores_gemma":[0.00002433449,0.00006781884,0.0005959804,0.0003654336,0.0001185054,0.0001343523,0.00008259786,0.00006862538,0.00001261275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006406639,"about_ca_system_score_gemma":0.000005371522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001913791,"about_ca_topic_score_gemma":0.0001352986,"domain_scores_codex":[0.9984112,0.00003975514,0.0009524541,0.0001530269,0.0002674003,0.0001760961],"domain_scores_gemma":[0.9976302,0.00005163616,0.002042112,0.0001985549,0.00002541833,0.0000520558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000469162,0.0001260984,0.9721943,0.00003321774,0.01872135,0.00001505805,0.000225962,0.007044671,0.00003291231,0.000007884501,0.0007013381,0.0008502828],"study_design_scores_gemma":[0.0002130886,0.0003362142,0.9385343,0.00000300641,0.05739606,0.000006338561,0.000383804,0.00007220831,0.0001102889,0.0000478271,0.002806261,0.00009058958],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979422,0.00001590336,0.0004057071,0.000543792,0.00007036519,0.0003031403,0.000005253555,0.000003996144,0.0007096481],"genre_scores_gemma":[0.9930869,0.00001245966,0.004847405,0.0003428889,0.00001457268,0.00001482418,0.000002278571,0.000006534307,0.001672099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03867471,"threshold_uncertainty_score":0.7865827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03829103055293113,"score_gpt":0.2708311043462565,"score_spread":0.2325400737933254,"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."}}