{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006430335,0.0004819657,0.000378807,0.0004512115,0.0002601467,0.0006932856,0.0006755141,0.0005558528,0.001476201],"category_scores_gemma":[0.0009302974,0.0003805212,0.000232558,0.0007624268,0.0003918815,0.001376378,0.0004576349,0.0006273635,0.0009915238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001851636,"about_ca_system_score_gemma":0.000316123,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009303809,"about_ca_topic_score_gemma":0.03597764,"domain_scores_codex":[0.9998991,0.00001905507,0.000005152192,0.00002670895,0.00004224361,0.000007754668],"domain_scores_gemma":[0.9997522,0.0001651746,0.00001596992,0.00001536035,0.00004236318,0.000008908712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00004818435,0.0000430338,0.01369658,0.0001319176,0.00008029949,0.0001936732,0.0009668833,0.006879796,0.007541155,0.008156352,0.04085442,0.9214078],"study_design_scores_gemma":[0.00001822297,0.0002227792,0.1266892,0.0005502869,0.0003023488,0.004335846,0.002837286,0.2194642,0.03796499,0.1002303,0.5071295,0.000255064],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1073694,0.03847359,0.7981307,0.004890696,0.001380641,0.00003552755,0.0008170394,0.002515762,0.04638675],"genre_scores_gemma":[0.2632769,0.02637363,0.5245533,0.001852301,0.001310384,0.00008530798,0.001472618,0.001621593,0.179454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9906962,"threshold_uncertainty_score":0.01849931,"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."}}