{"id":"W4404997588","doi":"10.1016/j.eiar.2024.107738","title":"Does jurisdictional siloing increase or undermine the efficiency and efficacy of next-generation IA in federalist states? A Canadian example","year":2024,"lang":"en","type":"article","venue":"Environmental Impact Assessment Review","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of Manitoba; Vancouver Coastal Health","funders":"Social Sciences and Humanities Research Council; Social Sciences and Humanities Research Council of Canada","keywords":"Federalist; Political science; Public administration; Environmental science; Law","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008008791,0.0003610326,0.0003996351,0.00008196173,0.0003134594,0.0001755523,0.0002408031,0.00007716619,0.007037103],"category_scores_gemma":[0.00002032805,0.0001884403,0.0001488598,0.0003432934,0.0003826725,0.0007116511,0.0002076767,0.0003040918,0.00007508595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001976937,"about_ca_system_score_gemma":0.0001284427,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05925222,"about_ca_topic_score_gemma":0.02149587,"domain_scores_codex":[0.9975253,0.0002746817,0.0005959048,0.0005047975,0.0005916992,0.0005076654],"domain_scores_gemma":[0.9990023,0.0002084119,0.0001348172,0.0003034026,0.000001430789,0.0003495791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001018137,0.002684507,0.7952316,0.001577117,0.0004858098,0.0004018189,0.004260963,0.002602805,0.05712298,0.0004461384,0.01172008,0.1233644],"study_design_scores_gemma":[0.0009024384,0.0004824302,0.9710516,0.001204856,0.0002235603,0.0000740025,0.0004630818,0.009256152,0.0002750519,0.0001976248,0.01517806,0.0006911982],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905246,0.005602416,0.00009932847,0.001335981,0.000177559,0.001145545,0.0001270782,0.00002442377,0.0009630684],"genre_scores_gemma":[0.9758347,0.02237293,0.0001777787,0.0007507168,0.00006718469,0.00006895234,0.0002356872,0.0000345316,0.0004575244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.17582,"threshold_uncertainty_score":0.9963593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03162637189085239,"score_gpt":0.3379144581314524,"score_spread":0.3062880862406,"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."}}