{"id":"W2168490467","doi":"10.1002/aqc.990","title":"A multi‐attribute trade‐off approach for advancing the management of marine wildlife tourism: a quantitative assessment of heterogeneous visitor preferences","year":2008,"lang":"en","type":"article","venue":"Aquatic Conservation Marine and Freshwater Ecosystems","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Wildlife; Wildlife tourism; Visitor pattern; Tourism; Environmental resource management; Preference; Business; Marketing; Population; Wildlife management; Recreation; Geography; Wildlife conservation; Environmental planning; Ecology; Economics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006767337,0.000151001,0.000435748,0.00008813195,0.0001148785,0.00001799061,0.0001366504,0.00005128404,0.00008330467],"category_scores_gemma":[0.00001437507,0.0001302788,0.00008805856,0.00008152561,0.00007327715,0.0001554988,0.0001047495,0.00005283618,0.000003360518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006040044,"about_ca_system_score_gemma":0.0000130797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0035615,"about_ca_topic_score_gemma":0.002367947,"domain_scores_codex":[0.9985237,0.00004018004,0.0009137528,0.000294415,0.00005888386,0.0001691217],"domain_scores_gemma":[0.9989558,0.0001233635,0.0006343012,0.0002298505,0.00001731098,0.0000393033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000215842,0.0001350216,0.9940954,0.0003546662,0.0002729386,8.50944e-7,0.0004333285,0.001053108,0.00003488542,0.002815592,0.0002702851,0.0005123675],"study_design_scores_gemma":[0.001376096,0.0002164855,0.1832342,0.00003302618,0.00004387488,0.000007991531,0.0004596605,0.811247,0.00008538595,0.0008466319,0.002274531,0.0001751226],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9456526,0.0001933538,0.05217707,0.0003553787,0.0001056777,0.001006783,0.0001422238,0.000009929327,0.0003569855],"genre_scores_gemma":[0.9503605,0.0004669868,0.04829783,0.0001030207,0.00002676262,0.0002276629,0.0002410567,0.00001496313,0.0002612546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8108612,"threshold_uncertainty_score":0.5383947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09070868901483786,"score_gpt":0.2506582819684325,"score_spread":0.1599495929535946,"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."}}