{"id":"W2100531623","doi":"10.1071/wr14069","title":"Using novel spatial mark–resight techniques to monitor resident Canada geese in a suburban environment","year":2015,"lang":"en","type":"article","venue":"Wildlife Research","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Animal and Plant Health Inspection Service; North Carolina Department of Transportation; North Carolina State University","keywords":"Goose; Geography; Context (archaeology); Waterfowl; Population; Wildlife management; Wildlife; Flyway; Range (aeronautics); Branta; Ecology; Demography; Biology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002031485,0.0001587459,0.000180709,0.0001700247,0.0001908052,0.00003911528,0.0004536717,0.0001308308,0.0005546845],"category_scores_gemma":[0.000346042,0.0001595249,0.00002375258,0.0004798336,0.0001940306,0.0001898683,0.0005902714,0.0004209349,0.0002326667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002991109,"about_ca_system_score_gemma":0.0004169013,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8123981,"about_ca_topic_score_gemma":0.6611603,"domain_scores_codex":[0.9968061,0.0003464512,0.0003214839,0.0004982555,0.001312185,0.0007155507],"domain_scores_gemma":[0.9989207,0.000150328,0.00004675726,0.000424702,0.0000286542,0.0004288027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001445927,0.0001140003,0.9277599,0.000004860041,0.00000603077,0.00006472439,0.0002958025,0.001308687,0.002236634,0.00002818236,0.06678197,0.001254612],"study_design_scores_gemma":[0.0004834967,0.0001863737,0.9073837,0.00003969796,0.000004362629,0.00001152182,0.0003638066,0.001920823,0.001162185,0.0002408596,0.08790144,0.0003017789],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902098,0.00002557976,0.0007081754,0.006084083,0.0001172437,0.0007424101,0.000009523727,0.00002346588,0.002079678],"genre_scores_gemma":[0.9932822,0.00001078327,0.003925647,0.001134357,0.000167642,0.0001494685,0.000006133189,0.00002444367,0.001299311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1512378,"threshold_uncertainty_score":0.7821646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08906570813751805,"score_gpt":0.3286724596957487,"score_spread":0.2396067515582306,"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."}}