{"id":"W1760896667","doi":"10.1007/978-0-387-78151-8_20","title":"Filling a Void: Abundance Estimation of North American Populations of Arctic Geese Using Hunter Recoveries","year":2008,"lang":"en","type":"book-chapter","venue":"","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Abundance (ecology); Waterfowl; Estimation; Geography; Arctic; Abundance estimation; Inference; Statistics; Ecology; Biology; Habitat; Computer science; Mathematics; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006793913,0.0001808866,0.0004462012,0.0001175352,0.00007989706,0.000004716705,0.0001787857,0.00006356816,0.002254887],"category_scores_gemma":[0.00005133631,0.0001793177,0.0001414852,0.0001161431,0.0006803602,0.0001587558,0.0001277965,0.0001308969,0.0000725033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002179937,"about_ca_system_score_gemma":0.00001896399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003578558,"about_ca_topic_score_gemma":0.01685458,"domain_scores_codex":[0.9987537,0.00001945245,0.0005392999,0.0002761389,0.0002599048,0.0001514629],"domain_scores_gemma":[0.9988083,0.00005639134,0.0007257388,0.0003484475,0.00002786913,0.000033244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00003120778,0.00007266821,0.3573144,0.00006636314,0.0001579442,0.000008455397,0.0005798535,0.6137176,0.0001389872,0.0006637827,0.0003972143,0.02685152],"study_design_scores_gemma":[0.0003837274,0.0004758291,0.7911606,0.0002571589,0.0006910821,0.00006718798,0.00008348791,0.1947993,0.0005507165,0.003471796,0.006707362,0.001351767],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8919026,0.00003645121,0.01510396,0.00004338583,0.0001278702,0.0003442329,0.0000470123,0.00002760956,0.09236687],"genre_scores_gemma":[0.917159,0.000119402,0.05236139,0.00007096535,0.00001948894,0.000003865072,0.00005059618,0.00003061556,0.03018475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4338462,"threshold_uncertainty_score":0.9986572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02559030522955081,"score_gpt":0.2543752495641528,"score_spread":0.2287849443346019,"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."}}