{"id":"W1968854538","doi":"10.1007/s10661-005-9098-0","title":"Development of a New Approach to Cumulative Effects Assessment: A Northern River Ecosystem Example","year":2006,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; Parks Canada; University of New Brunswick; Environment and Climate Change Canada","funders":"","keywords":"Cumulative effects; Baseline (sea); Aquatic ecosystem; Environmental science; Environmental resource management; Ecosystem; Environmental monitoring; Water quality; Sustainable development; Ecosystem health; Environmental planning; Environmental impact assessment; Process (computing); Environmental protection; Water resource management; Ecosystem services; Ecology; Environmental engineering; Fishery; Computer 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":[0.003100815,0.0006738889,0.0007878828,0.001792774,0.001166603,0.002767663,0.001313512,0.0009347955,0.003525989],"category_scores_gemma":[0.003676192,0.0003105578,0.001182716,0.001526754,0.001038565,0.002957745,0.001889989,0.001410091,0.0003842536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001748911,"about_ca_system_score_gemma":0.001872284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02335104,"about_ca_topic_score_gemma":0.06208526,"domain_scores_codex":[0.9990368,0.0003648711,0.00006007517,0.0001149854,0.0003777613,0.00004562987],"domain_scores_gemma":[0.9981784,0.0007126307,0.0000875975,0.0002258595,0.0007088901,0.00008671131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001120047,0.0002944759,0.01742806,0.0003012189,0.0003697269,0.001223748,0.001442065,0.2166828,0.01153604,0.3460307,0.01000045,0.3945787],"study_design_scores_gemma":[0.0000630195,0.0002192633,0.00759474,0.0001169883,0.000242351,0.0009910535,0.0008999444,0.6414062,0.004099248,0.2786278,0.06564072,0.00009852443],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02715374,0.000544223,0.9479284,0.001640006,0.00007759804,0.0001561143,0.000245123,0.0003072002,0.02194769],"genre_scores_gemma":[0.1991685,0.001280562,0.7855503,0.0002352139,0.00008908405,0.0002718738,0.0001724661,0.0001446592,0.01308745],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02335104,"threshold_uncertainty_score":0.04643023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01952433111227052,"score_gpt":0.2754094772550352,"score_spread":0.2558851461427646,"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."}}