{"id":"W2560229779","doi":"10.1016/j.ocecoaman.2016.11.026","title":"Identifying culturally significant areas for marine spatial planning","year":2016,"lang":"en","type":"article","venue":"Ocean & Coastal Management","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":135,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Fredericton; University of British Columbia; Mount Allison University","funders":"","keywords":"Structuring; Marine spatial planning; Cultural values; Narrative; Cultural issues; Cultural diversity; Environmental resource management; Marine ecosystem; Cultural identity; Geography; Sociology; Environmental planning; Ecosystem; Political science; Ecology; Social science; Anthropology; Environmental 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":[0.0009897593,0.0003338054,0.0002229916,0.002255956,0.001998691,0.003044156,0.0007020175,0.0004067103,0.009356425],"category_scores_gemma":[0.007732566,0.0002639068,0.0003237274,0.003451647,0.001037891,0.002156388,0.002824369,0.0006272733,0.0004769328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00297991,"about_ca_system_score_gemma":0.007500696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08132972,"about_ca_topic_score_gemma":0.2555239,"domain_scores_codex":[0.9992305,0.0004199356,0.0000411598,0.00006944853,0.000106856,0.000132018],"domain_scores_gemma":[0.9976739,0.0009398704,0.0002852981,0.0002325695,0.0006192267,0.0002490304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002162577,0.0003424395,0.547308,0.000579384,0.0001023654,0.00121718,0.04017816,0.01321692,0.006675226,0.1112133,0.01310191,0.2658489],"study_design_scores_gemma":[0.00006169822,0.0001656799,0.2999167,0.00121987,0.0002053569,0.0007077869,0.4654448,0.03623589,0.005117996,0.1195917,0.07121913,0.0001133932],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8905542,0.0004824336,0.02380297,0.003701408,0.00003347511,0.0003712859,0.001658333,0.00008344316,0.07931251],"genre_scores_gemma":[0.9736856,0.0002707115,0.02360493,0.00006424973,0.000004025846,0.0001512987,0.0004183729,0.0000203728,0.001780462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08132972,"threshold_uncertainty_score":0.1617126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01433877144371178,"score_gpt":0.2310683407403954,"score_spread":0.2167295692966836,"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."}}