{"id":"W2909246210","doi":"10.1002/pan3.10081","title":"Scientific shortcomings in environmental impact statements internationally","year":2020,"lang":"en","type":"article","venue":"People and Nature","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology; Fisheries and Oceans Canada; World Wildlife Fund Canada; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Pacific Institute for Climate Solutions; National Science Foundation","keywords":"Credibility; Judgement; Scope (computer science); Transparency (behavior); Process (computing); Environmental impact assessment; Sample (material); Impact assessment; Environmental resource management; Scale (ratio); Sustainable development; Environmental planning; Precautionary principle; Business; Risk analysis (engineering); Computer science; Political science; Environmental science; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3794393,0.001265151,0.001371132,0.02551881,0.006486656,0.03230646,0.00756458,0.010363,0.01268585],"category_scores_gemma":[0.6426172,0.001530486,0.001819403,0.02868818,0.02137041,0.0315812,0.01714746,0.0166191,0.002709906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009720761,"about_ca_system_score_gemma":0.02174231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00387663,"about_ca_topic_score_gemma":0.002168327,"domain_scores_codex":[0.6357167,0.1534194,0.0421177,0.01425571,0.1482339,0.006256507],"domain_scores_gemma":[0.1885751,0.584433,0.04245991,0.04163578,0.1397906,0.003105639],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00008176856,0.00008067062,0.005533061,0.00175187,0.0001079695,0.0005218873,0.01405819,0.003208694,0.0005343764,0.7057326,0.1020382,0.1663507],"study_design_scores_gemma":[0.0000420633,0.00009684126,0.007050422,0.007611332,0.0001209616,0.0004405214,0.01530954,0.002933348,0.002104545,0.3791682,0.584956,0.0001662606],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02414993,0.01686961,0.06758754,0.5287191,0.01890298,0.0005882782,0.001705128,0.0008729157,0.3406045],"genre_scores_gemma":[0.7252496,0.01893919,0.07952919,0.1202124,0.01615724,0.001505195,0.002768516,0.001353235,0.03428536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6205606,"threshold_uncertainty_score":0.7652618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008076922080402369,"score_gpt":0.2977581122923269,"score_spread":0.2896811902119245,"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."}}