{"id":"W2043372779","doi":"10.1016/s0964-5691(02)00121-7","title":"Lessons learned from ‘decentralized’ ICM: an analysis of Canada's Atlantic Coastal Action Program and China's Xiamen ICM Program","year":2003,"lang":"en","type":"article","venue":"Ocean & Coastal Management","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Australian Centre for Advanced Photovoltaics","keywords":"Stakeholder; Action plan; Government (linguistics); China; Environmental resource management; Environmental planning; Business; Political science; Geography; Ecology; Public relations; Environmental science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003130535,0.0003743139,0.0004563578,0.0001632387,0.0002176867,0.0001467283,0.0003307848,0.00005347399,0.0009871145],"category_scores_gemma":[0.00001496216,0.0003587246,0.0001385907,0.000934688,0.0001946668,0.0002518457,0.001645542,0.0001462314,0.000008229423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001799646,"about_ca_system_score_gemma":0.00002871924,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4252125,"about_ca_topic_score_gemma":0.8280192,"domain_scores_codex":[0.9970952,0.0001484736,0.0004450092,0.0008486126,0.000784766,0.0006779634],"domain_scores_gemma":[0.9988133,0.00002144581,0.0002279799,0.0005962662,0.00001603114,0.0003249492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001522132,0.001696786,0.07238027,0.0001035027,0.001287486,0.0001033884,0.0002633656,0.003167577,0.000124685,0.004809948,0.00364525,0.9122655],"study_design_scores_gemma":[0.001715623,0.0006977507,0.7095152,0.00003847993,0.002241419,0.000003808536,0.002366879,0.01005821,0.0001534441,0.002524707,0.2698041,0.00088034],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9388679,0.00002114564,0.0008233644,0.0009754509,0.0001826979,0.00187779,0.0001473699,0.0002200216,0.05688423],"genre_scores_gemma":[0.9926477,0.0002341757,0.003275455,0.00009496618,0.00001481708,0.00006117785,0.0004408453,0.00003259801,0.003198241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9113852,"threshold_uncertainty_score":0.9999261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01943099107976618,"score_gpt":0.2658330663081877,"score_spread":0.2464020752284215,"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."}}