{"id":"W4393199441","doi":"10.1080/14616688.2024.2332368","title":"National tourism organizations and climate change","year":2024,"lang":"en","type":"article","venue":"Tourism Geographies","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tourism; Climate change; Relevance (law); Business; Market segmentation; Rebranding; Sample (material); Economic geography; Economy; Marketing; Geography; Political science; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006044075,0.00008455941,0.0001019084,0.0008938697,0.001525918,0.001936487,0.0002539868,0.0004362778,0.01915145],"category_scores_gemma":[0.00212037,0.00004265186,0.0001729874,0.002274513,0.001072912,0.0009361035,0.001635507,0.0006341623,0.0007083329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001824432,"about_ca_system_score_gemma":0.001824028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01872724,"about_ca_topic_score_gemma":0.04136292,"domain_scores_codex":[0.9992573,0.0002968643,0.00002171648,0.00003783395,0.0001020652,0.0002842305],"domain_scores_gemma":[0.9974751,0.0004609072,0.0007687044,0.00009652547,0.000327606,0.0008711517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001678499,0.000566923,0.6689329,0.0003871285,0.00008212695,0.0006826437,0.01595292,0.001106725,0.0001921527,0.1054699,0.06167366,0.1447851],"study_design_scores_gemma":[0.00001418698,0.0000838382,0.7281796,0.0002410954,0.00001995335,0.0002786227,0.05478817,0.0004350238,0.00007294876,0.007862358,0.2080017,0.00002240237],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.574658,0.006450853,0.0003657223,0.02014999,0.0003803921,0.00003731348,0.0008969448,0.00002774764,0.397033],"genre_scores_gemma":[0.9836708,0.002289714,0.0001404081,0.0007461537,0.0001591653,0.00002055824,0.0003783736,0.000009767153,0.01258507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01915145,"threshold_uncertainty_score":0.06406796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0263778516162683,"score_gpt":0.3206004497152246,"score_spread":0.2942225980989562,"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."}}