{"id":"W4225144605","doi":"10.1142/s1464333222500120","title":"Overcoming Divisive Strategic Environmental Assessments for Offshore Oil and Gas in Nova Scotia, Canada","year":2021,"lang":"en","type":"article","venue":"Journal of Environmental Assessment Policy and Management","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"College of the North Atlantic; Balsillie School of International Affairs; University of Waterloo; York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Nova scotia; Offshore oil and gas; Stakeholder; Scope (computer science); Credibility; Government (linguistics); Environmental planning; Business; Environmental resource management; Submarine pipeline; Function (biology); Strategic environmental assessment; Political science; Environmental protection; Environmental impact assessment; Geography; Environmental science; Engineering; Public relations","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004454901,0.0004312248,0.0005372762,0.0001284515,0.0002019758,0.0001142702,0.0002561395,0.0001042984,0.0006206774],"category_scores_gemma":[0.000009163799,0.0004262709,0.0001297845,0.0001567391,0.0002699704,0.0006009993,0.0007297286,0.000322039,0.00000597944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002494361,"about_ca_system_score_gemma":0.0001094867,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01187663,"about_ca_topic_score_gemma":0.03524571,"domain_scores_codex":[0.9969604,0.000144879,0.0008190668,0.0005308602,0.0008955942,0.0006492275],"domain_scores_gemma":[0.9988,0.0001212264,0.0004618205,0.0002431343,0.000002944357,0.0003708726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000250584,0.003254329,0.7895165,0.000367688,0.0008941932,0.001356991,0.0007730991,0.001062338,0.04143973,0.003071618,0.001604089,0.1564088],"study_design_scores_gemma":[0.004926194,0.0005442979,0.9698789,0.0001614771,0.0002386449,0.0001946487,0.007183291,0.0004533687,0.0008470459,0.002810942,0.0119736,0.0007876274],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9876949,0.0002883272,0.0001166149,0.001207822,0.0002441328,0.0002574392,0.0001483392,0.000005102259,0.01003731],"genre_scores_gemma":[0.9894035,0.003665334,0.004058185,0.001033095,0.000126101,0.00001730127,0.00004395962,0.00004088551,0.001611584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1803623,"threshold_uncertainty_score":0.9998189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01583847862005451,"score_gpt":0.2934530276075301,"score_spread":0.2776145489874756,"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."}}