{"id":"W2791249411","doi":"10.1126/sciadv.aao0167","title":"Hallmarks of science missing from North American wildlife management","year":2018,"lang":"en","type":"article","venue":"Science Advances","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"Raincoast Conservation Foundation; Tula Foundation; University of Victoria; Simon Fraser University","funders":"Hakai Institute; Pacific Salmon Foundation; Tula Foundation; Simon Fraser University; Wilburforce Foundation","keywords":"Wildlife; Wildlife management; State (computer science); State management; Geography; Environmental resource management; Data science; Computer science; Biology; Ecology; Environmental science","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005992049,0.00009430002,0.0001183065,0.0001060928,0.0007820743,0.00003707684,0.0009279014,0.00001032137,0.0002450634],"category_scores_gemma":[0.0001132324,0.00008304637,0.00001965525,0.002528994,0.02287575,0.001570315,0.000337152,0.00005372331,0.0001633066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001149257,"about_ca_system_score_gemma":0.00006705478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002997095,"about_ca_topic_score_gemma":0.0008864787,"domain_scores_codex":[0.9982062,0.00001852213,0.0001967218,0.0005269633,0.0006653949,0.0003862254],"domain_scores_gemma":[0.9992707,0.00004151102,0.0001916618,0.0003359885,0.0000401733,0.0001199924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001183297,0.00003068591,0.8504429,0.000001601374,0.00000170541,0.000001354126,0.000285389,0.0001126555,0.005151897,0.00009633903,0.0001939941,0.1436696],"study_design_scores_gemma":[0.00007646688,0.0000916353,0.9851121,0.000009666003,0.00000548498,7.84854e-7,0.00032012,0.0004571749,0.006621343,0.0008817193,0.006312427,0.0001110372],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827805,0.00001697623,0.0007074366,0.000689221,0.0003157247,0.00009874751,0.000002350097,0.00002509086,0.01536396],"genre_scores_gemma":[0.9776642,0.00001412722,0.02064307,0.001514656,0.00004034298,0.000005577225,7.953212e-7,0.00000328377,0.0001139717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1435586,"threshold_uncertainty_score":0.9797834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007701581619329071,"score_gpt":0.2487512087754637,"score_spread":0.2410496271561346,"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."}}