{"id":"W1994123841","doi":"10.1071/wr11105","title":"Assessment of bias in US waterfowl harvest estimates","year":2012,"lang":"en","type":"article","venue":"Wildlife Research","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Waterfowl; Anas; Goose; Branta; Geography; Context (archaeology); Anatidae; Fishery; Biology; Ecology; Habitat; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.07091466,0.0005762373,0.0005477831,0.002965952,0.0006819125,0.001309136,0.0009841589,0.0005684328,0.000972891],"category_scores_gemma":[0.1815939,0.0003371268,0.000879011,0.004149007,0.001075541,0.001079058,0.001973605,0.0006213629,0.0001922858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001647273,"about_ca_system_score_gemma":0.001619581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02093683,"about_ca_topic_score_gemma":0.01818727,"domain_scores_codex":[0.9460443,0.03200052,0.007044907,0.004806476,0.009155865,0.0009480189],"domain_scores_gemma":[0.8388612,0.08545853,0.04049174,0.01187462,0.02262914,0.0006848011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001404329,0.00001705572,0.9535664,0.0003288075,0.0009230702,0.00006832935,0.001513629,0.001219951,0.0003196413,0.0010397,0.001970601,0.03889231],"study_design_scores_gemma":[0.00002221495,0.0001404012,0.9743875,0.0005237364,0.0005455946,0.0004183709,0.001059363,0.005030319,0.001565366,0.003302242,0.0129469,0.00005805097],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9100591,0.009123323,0.06256355,0.002214593,0.0004577126,0.0004555536,0.00589319,0.000293677,0.00893942],"genre_scores_gemma":[0.9818906,0.0007354653,0.01407071,0.0007487105,0.0001237661,0.0002602407,0.001738215,0.00004575966,0.0003866311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07091466,"threshold_uncertainty_score":0.3750371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4965470248049577,"score_gpt":0.5373102824956577,"score_spread":0.04076325769069999,"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."}}