{"id":"W2770062549","doi":"10.1017/s0030605317001557","title":"IUCN's encounter with 007: safeguarding consensus for conservation","year":2017,"lang":"en","type":"article","venue":"Oryx","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"IUCN Red List; Safeguarding; Vetting; Political science; Geography; IUCN protected area categories; Ecology; Law; Biology; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0002214642,0.00007200852,0.00008057534,0.000009701946,0.0005608248,0.00004443119,0.00014824,0.00005650364,0.0004583546],"category_scores_gemma":[0.000117815,0.00006103484,0.00002330093,0.00001914693,0.0003121013,0.0001748001,0.00004295978,0.00004844659,0.0001968071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004911944,"about_ca_system_score_gemma":0.00001505882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001667962,"about_ca_topic_score_gemma":0.0006177968,"domain_scores_codex":[0.9994828,0.00001630043,0.00009172032,0.0001760228,0.00008421291,0.0001489782],"domain_scores_gemma":[0.9994805,0.00008621232,0.0001224333,0.0002661708,0.00001343487,0.0000312248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009479207,0.00001455294,0.970174,0.000003715179,0.00001027062,0.000003740484,0.0000840529,0.00003548909,0.0005193222,0.0006279828,0.02722207,0.00121001],"study_design_scores_gemma":[0.0006718196,0.00008891131,0.9547018,0.00001133654,0.00001727227,0.000008806613,0.0000561679,0.0007331148,0.0004325288,0.0007494515,0.04241295,0.0001158042],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726602,0.000002701792,0.0011188,0.006445932,0.000178641,0.0002398351,0.000005193843,0.00002485954,0.0193238],"genre_scores_gemma":[0.9931122,9.498013e-7,0.001967256,0.001738286,0.00005339103,0.00004499507,0.000005905026,0.000007834664,0.003069147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.020452,"threshold_uncertainty_score":0.5018661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01634576258094049,"score_gpt":0.2414670092718039,"score_spread":0.2251212466908634,"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."}}