{"id":"W2751220450","doi":"10.1111/cobi.13008","title":"Equity trade‐offs in conservation decision making","year":2017,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Australian Research Council; Social Sciences and Humanities Research Council of Canada; Liber Ero Foundation; Fulbright Canada","keywords":"Equity (law); Conceptualization; Public economics; Equity theory; Deliberation; Business; Economics; Political science; Computer science; Microeconomics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006747694,0.0001409032,0.0001704259,0.00008471694,0.0006326698,0.00009859322,0.0005579566,0.0001501259,0.0008342956],"category_scores_gemma":[0.0004286513,0.0001368133,0.00005066635,0.0001385294,0.0004074669,0.0002830588,0.0007573597,0.0001165623,0.000221175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001914215,"about_ca_system_score_gemma":0.00002073489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001687803,"about_ca_topic_score_gemma":0.004722741,"domain_scores_codex":[0.9987574,0.00009429603,0.0003118101,0.0003922257,0.0001638686,0.0002804214],"domain_scores_gemma":[0.9989866,0.000164328,0.0002726797,0.0005122707,0.00001444566,0.00004968725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004432412,0.00003979967,0.9589217,0.000005519766,0.000005380101,0.000004570555,0.000163098,0.0000331132,0.001105573,0.0003730663,0.002856776,0.0364471],"study_design_scores_gemma":[0.0005461128,0.00003295788,0.9235997,0.00002414316,0.000007992719,0.000001687928,0.0000776327,0.002455579,0.00006548088,0.004337813,0.06869788,0.0001530537],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9723129,0.00002407415,0.00217214,0.01399093,0.000333795,0.0003058259,0.0000085796,0.00004378374,0.01080791],"genre_scores_gemma":[0.9934897,0.00003627139,0.001588494,0.004558701,0.0000369658,0.00001415467,0.00002829471,0.000006367763,0.0002409887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06584111,"threshold_uncertainty_score":0.9134952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05705919700277656,"score_gpt":0.3104301120884118,"score_spread":0.2533709150856353,"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."}}