{"id":"W2025761838","doi":"10.1142/s1464333212500159","title":"ADVANCING A NATIONAL STRATEGIC ENVIRONMENTAL ASSESSMENT FOR THE CANADIAN OFFSHORE OIL AND GAS INDUSTRY WITH SPECIAL EMPHASIS ON CUMULATIVE EFFECTS","year":2012,"lang":"en","type":"article","venue":"Journal of Environmental Assessment Policy and Management","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Industry Canada; Strategic Research Council; Beaufort Regional Environmental Assessment","keywords":"Strategic environmental assessment; Cumulative effects; Offshore oil and gas; Sustainability; Submarine pipeline; Environmental impact assessment; Environmental planning; Business; Environmental resource management; Process (computing); Wildlife; Environmental science; Petroleum industry; Environmental protection; Natural resource economics; Engineering; Environmental engineering; Ecology; Economics; Computer science","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":[0.000872039,0.000439821,0.0003604734,0.0001798064,0.0008815151,0.0001376317,0.0002571593,0.00016505,0.0004274616],"category_scores_gemma":[0.000009501709,0.0003121801,0.0001235491,0.0001267751,0.0005456889,0.0007356132,0.0002614299,0.0005563283,0.00001109193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003544978,"about_ca_system_score_gemma":0.00007719708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008022051,"about_ca_topic_score_gemma":0.001249145,"domain_scores_codex":[0.9970257,0.0001409703,0.0004825582,0.0003443458,0.001211289,0.0007951668],"domain_scores_gemma":[0.9984488,0.0002550126,0.0004290066,0.0001841405,0.000003507852,0.0006794884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007531229,0.005740635,0.6208014,0.0003025444,0.003116561,0.0001968775,0.004368718,0.005332948,0.003710478,0.03445081,0.005333314,0.3158926],"study_design_scores_gemma":[0.002860339,0.001248679,0.9524421,0.00008961256,0.0003417642,0.00009602118,0.003706903,0.0003416353,0.0001162912,0.001511874,0.03671792,0.0005268496],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9565387,0.0001507914,0.0001246736,0.003057336,0.0003095171,0.0007247666,0.000143845,0.00000897625,0.03894136],"genre_scores_gemma":[0.9922015,0.001339716,0.002815128,0.001618648,0.0009261424,0.00009123687,0.00002284124,0.00004218184,0.0009425785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3316407,"threshold_uncertainty_score":0.999933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01489945226029901,"score_gpt":0.3060123522501266,"score_spread":0.2911128999898276,"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."}}