{"id":"W4238519492","doi":"10.2172/828059","title":"Supplement Analysis for the Wildlife Mitigation Program EIS (DOE/EIS-0246/SA-36)","year":2003,"lang":"en","type":"report","venue":"","topic":"Rangeland and Wildlife Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bonneville Power Administration; U.S. Department of Energy","keywords":"Wildlife; Liability; Remedial action; Tribe; Remedial education; State (computer science); Compensation (psychology); Environmental planning; Geography; Political science; Law; Environmental remediation; Ecology; Computer science; Psychology; Contamination","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005640734,0.0008278342,0.0006157494,0.007023253,0.001722942,0.002338129,0.002282584,0.001060776,0.4046343],"category_scores_gemma":[0.0230532,0.0005452348,0.0008873115,0.005980027,0.0002665282,0.001720962,0.001591322,0.001220467,0.09806187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002928757,"about_ca_system_score_gemma":0.00904993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04278979,"about_ca_topic_score_gemma":0.05378859,"domain_scores_codex":[0.9937338,0.000818642,0.0004917915,0.0004656663,0.004071714,0.0004184908],"domain_scores_gemma":[0.9753301,0.002994489,0.001516526,0.002180576,0.01732745,0.0006508816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000182407,0.00013137,0.003098365,0.0003999973,0.00002695054,0.00005326161,0.00008477078,0.0003670776,0.0007635127,0.003289325,0.9418191,0.04978393],"study_design_scores_gemma":[0.00004568686,0.00008573544,0.01217733,0.0002291111,0.00002365035,0.00003830704,0.0002616733,0.0004362684,0.001070244,0.001283837,0.9843249,0.00002313335],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.00654341,0.0002188895,0.007467913,0.002714002,0.001334387,0.004826828,0.7143976,0.002555073,0.2599419],"genre_scores_gemma":[0.02384584,0.0006330943,0.03938304,0.001813224,0.000377862,0.006872679,0.6907212,0.001836568,0.2345165],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4046343,"threshold_uncertainty_score":0.8492169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0263875282884862,"score_gpt":0.2942050728074206,"score_spread":0.2678175445189344,"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."}}