{"id":"W2413737462","doi":"10.1016/j.envsci.2016.05.018","title":"A multiple timescales approach to assess urgency in adaptation to climate change with an application to the tourism industry","year":2016,"lang":"en","type":"article","venue":"Environmental Science & Policy","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Ouranos","funders":"Fonds de recherche du Québec – Nature et technologies; Compute Canada; McGill University","keywords":"Vulnerability (computing); Adaptation (eye); Computer science; Climate change; Tourism; Mainstream; Simple (philosophy); Data science; Environmental resource management; Risk analysis (engineering); Business; Environmental science; Geography; Computer security; Political science; Ecology; Psychology","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":[0.004564549,0.0008971145,0.0005094121,0.006756544,0.001286789,0.003077246,0.001050845,0.001557101,0.01160085],"category_scores_gemma":[0.01547149,0.0004347227,0.001706462,0.004455838,0.002103388,0.004513699,0.002923847,0.001756674,0.0006224473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00288757,"about_ca_system_score_gemma":0.001621331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01709192,"about_ca_topic_score_gemma":0.01723522,"domain_scores_codex":[0.9974069,0.001388669,0.0001720147,0.000411477,0.0004457194,0.0001751888],"domain_scores_gemma":[0.9917691,0.00565464,0.0009582989,0.0003953617,0.0007224461,0.0005000862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005904931,0.0007208866,0.1211291,0.001063217,0.0006638055,0.001340837,0.0216618,0.1775975,0.01047651,0.3737015,0.008098138,0.2829562],"study_design_scores_gemma":[0.00006349048,0.0004949183,0.07946115,0.000244128,0.0001818078,0.000640717,0.01792922,0.5607774,0.00179218,0.314212,0.02393143,0.0002714657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1584107,0.0008359734,0.7852777,0.003121206,0.0002512998,0.0006159368,0.001486915,0.0007517865,0.04924852],"genre_scores_gemma":[0.746477,0.0003063523,0.249443,0.0001602563,0.00006541521,0.0003656849,0.0002905274,0.00009554434,0.00279626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01709192,"threshold_uncertainty_score":0.0388087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.272581541708411,"score_gpt":0.4033173551921818,"score_spread":0.1307358134837708,"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."}}