{"id":"W2110293907","doi":"10.1016/j.jenvman.2004.03.006","title":"Cumulative environmental impacts and integrated coastal management: the case of Xiamen, China","year":2004,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":115,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"China; Environmental science; Environmental impact assessment; Environmental resource management; Environmental protection; Environmental planning; Geography; Ecology; Archaeology","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":[0.0007663209,0.0004197136,0.0004428802,0.001528081,0.002198649,0.003216695,0.001589432,0.00152766,0.004173134],"category_scores_gemma":[0.001687751,0.0003153296,0.0007041784,0.003703692,0.002053321,0.001812327,0.003039527,0.0007922929,0.0001187107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01152312,"about_ca_system_score_gemma":0.005095801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3680379,"about_ca_topic_score_gemma":0.5253068,"domain_scores_codex":[0.9995011,0.00009444998,0.00001828738,0.00004936548,0.00006223663,0.0002746826],"domain_scores_gemma":[0.9992403,0.0001791888,0.0001739022,0.00005293408,0.0001254357,0.0002283291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007305224,0.000711327,0.6212669,0.0001825029,0.0006516756,0.02333542,0.007949417,0.1916791,0.0021262,0.101285,0.003524114,0.04655787],"study_design_scores_gemma":[0.0002821407,0.0006714319,0.6522369,0.0001555179,0.001151944,0.001877799,0.04986325,0.2268293,0.001300633,0.04997947,0.01538877,0.0002628624],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929062,0.0002437333,0.0002920089,0.0005626856,0.000004903445,0.00001812346,0.0000679249,0.000007571895,0.00589692],"genre_scores_gemma":[0.9984444,0.0001602182,0.0001026549,0.00002895285,0.000003680959,0.000005451915,0.0000278125,0.000001464545,0.001225487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3680379,"threshold_uncertainty_score":0.7317913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003854818654247006,"score_gpt":0.193668715684296,"score_spread":0.189813897030049,"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."}}