{"id":"W1995659397","doi":"10.1016/j.marpol.2010.10.005","title":"Spatial characterization of marine recreational boating: Exploring the use of an on-the-water questionnaire for a case study in the Pacific Northwest","year":2010,"lang":"en","type":"article","venue":"Marine Policy","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vancouver Island University; University of Victoria","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Recreation; Respondent; TRIPS architecture; Data collection; Sample (material); Spatial analysis; Environmental resource management; Geography; Spatial distribution; Spatial planning; Geographic information system; Marine spatial planning; Environmental planning; Transport engineering; Environmental science; Cartography; Remote sensing; Ecology; Statistics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002343564,0.0001540129,0.0001803283,0.001524164,0.001091566,0.0007635058,0.0007086171,0.0006005699,0.001485816],"category_scores_gemma":[0.007903444,0.0001705708,0.0002024954,0.001948061,0.0006614881,0.001270873,0.0009308977,0.0004885964,0.0001592233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009777099,"about_ca_system_score_gemma":0.001166327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08588272,"about_ca_topic_score_gemma":0.2024068,"domain_scores_codex":[0.9990253,0.0006297688,0.00006076453,0.00008971615,0.00009588218,0.00009859107],"domain_scores_gemma":[0.9934722,0.003439225,0.001429408,0.0003731314,0.0009284256,0.0003576303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008477621,0.0002701392,0.8524889,0.0001176462,0.00003401469,0.0007107285,0.1240268,0.0004447504,0.002866541,0.0003828231,0.0004885143,0.01808429],"study_design_scores_gemma":[0.000002766634,0.0001303582,0.7559111,0.00004779908,0.00001285408,0.0002423364,0.2399139,0.001411784,0.0004298501,0.0001158428,0.001759184,0.00002222444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980025,0.00001889566,0.0004548644,0.00009707661,0.000001531665,0.0000376905,0.0001845632,0.00000454686,0.001198326],"genre_scores_gemma":[0.9978788,0.00005024928,0.00136866,0.00002663738,0.000001355731,0.00005307264,0.0001666892,0.000004275618,0.0004503115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08588272,"threshold_uncertainty_score":0.1707656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04452934491025107,"score_gpt":0.2563685900664043,"score_spread":0.2118392451561532,"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."}}