{"id":"W4413220769","doi":"10.22260/ccc2025/0044","title":"ASSESSMENT OF LOCAL ENVIRONMENTAL IMPACTS IN CONSTRUCTION PROJECTS USING A KPI-BASED APPROACH","year":2025,"lang":"en","type":"article","venue":"","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Environmental impact assessment; Computer science; Environmental science; Construction engineering; Engineering; Political science","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.003773857,0.001460707,0.0009442875,0.01137397,0.0007410449,0.004951871,0.001269879,0.0008785428,0.002022097],"category_scores_gemma":[0.008319861,0.0004715354,0.001160879,0.008288392,0.0008689177,0.003003609,0.003235317,0.0007450564,0.0003576112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003168419,"about_ca_system_score_gemma":0.002120933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01031214,"about_ca_topic_score_gemma":0.01423393,"domain_scores_codex":[0.9966072,0.001039509,0.0003361157,0.0003150013,0.001432871,0.0002693468],"domain_scores_gemma":[0.9960209,0.001450032,0.0008164678,0.0002641384,0.001208881,0.0002397807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002384707,0.0005560291,0.1007833,0.0009982045,0.0003576649,0.000657178,0.002158487,0.698996,0.007653729,0.02030941,0.001602995,0.1656885],"study_design_scores_gemma":[0.00002101662,0.0003400355,0.05594426,0.0002225117,0.0002011719,0.0002487992,0.006330706,0.9079577,0.005088449,0.01734314,0.006149803,0.0001523704],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5238958,0.0006214243,0.4349868,0.0005893605,0.00004483409,0.001195785,0.002916503,0.001117165,0.03463227],"genre_scores_gemma":[0.8920473,0.0003749317,0.1047136,0.00002053376,0.000008967131,0.0003696987,0.001145962,0.00004668048,0.001272492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01137397,"threshold_uncertainty_score":0.02298862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07361693522548866,"score_gpt":0.3869717471805968,"score_spread":0.3133548119551081,"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."}}