{"id":"W3215709335","doi":"10.1080/14693062.2021.2002251","title":"A global assessment of policy tools to support climate adaptation","year":2021,"lang":"en","type":"article","venue":"Climate Policy","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"China Scholarship Council; National Science Foundation of Sri Lanka; Social Sciences and Humanities Research Council of Canada; Portland State University; National Science Foundation","keywords":"Climate policy; Adaptation (eye); Environmental resource management; Climate change adaptation; Climate change; Natural resource economics; Business; Environmental science; Environmental economics; Economics; Environmental planning; Ecology","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":[0.09046362,0.001989843,0.002118999,0.02961465,0.00196761,0.01202697,0.002886521,0.003322158,0.01013867],"category_scores_gemma":[0.1457901,0.0009624963,0.003434936,0.0302483,0.005194494,0.01782415,0.009867805,0.00392216,0.00132813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01292045,"about_ca_system_score_gemma":0.04372054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01373851,"about_ca_topic_score_gemma":0.01910156,"domain_scores_codex":[0.9513845,0.02889886,0.00587059,0.002707954,0.009556547,0.001581403],"domain_scores_gemma":[0.8111239,0.136119,0.01324125,0.008895259,0.02820286,0.00241772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001703102,0.0001450135,0.01292835,0.1290683,0.00198822,0.0002843047,0.01003975,0.006575354,0.001518726,0.1634348,0.0323115,0.6415354],"study_design_scores_gemma":[0.0001063493,0.0002495671,0.02747362,0.2714816,0.003406766,0.0002807251,0.01593909,0.00197874,0.001613167,0.09045552,0.5867972,0.0002176478],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03825518,0.6693716,0.04617577,0.08077822,0.002968088,0.002679477,0.01420751,0.0007481367,0.144816],"genre_scores_gemma":[0.4488205,0.3911459,0.1260208,0.01817981,0.0006801531,0.004194386,0.007507623,0.000449091,0.003001742],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.09046362,"threshold_uncertainty_score":0.4784231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1484373073713381,"score_gpt":0.3594298751776898,"score_spread":0.2109925678063517,"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."}}