{"id":"W3090566432","doi":"10.5194/egusphere-egu2020-21004","title":"Modelling Historical Adaptation Rates to Inform Future Adaptation Pathways","year":2020,"lang":"en","type":"article","venue":"","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Adaptation (eye); Context (archaeology); Climate change; Benchmarking; Macro; Climate change adaptation; Set (abstract data type); Representative Concentration Pathways; Econometric model; Impact assessment; Computer science; Environmental resource management; Econometrics; Climate model; Economics; Geography; Ecology; Political 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004263657,0.0006558635,0.0004391339,0.001974057,0.0003706402,0.002587111,0.00130819,0.001423005,0.007678337],"category_scores_gemma":[0.02106426,0.000461807,0.0009361454,0.002225645,0.0006501386,0.003754568,0.001543131,0.00164276,0.0009256763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002058123,"about_ca_system_score_gemma":0.001363307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02131069,"about_ca_topic_score_gemma":0.0139066,"domain_scores_codex":[0.9991295,0.0004192358,0.0000721738,0.0002116012,0.00008760842,0.00007986397],"domain_scores_gemma":[0.9950734,0.003037092,0.0006378342,0.0005797085,0.0004894338,0.0001825771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000353502,0.00003220404,0.01955479,0.00009810206,0.00007595357,0.00009046855,0.0003065211,0.8702974,0.0002531957,0.08427855,0.00225471,0.02272273],"study_design_scores_gemma":[0.00001123536,0.00002074288,0.006896725,0.0001083647,0.00004680645,0.00004539545,0.0002404481,0.8712233,0.000285832,0.1113253,0.009754781,0.00004095751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3111237,0.001866238,0.6165841,0.005253504,0.0002908288,0.0002273398,0.008851887,0.001019179,0.05478317],"genre_scores_gemma":[0.9379533,0.001443023,0.05319974,0.0001529544,0.00004349301,0.0002119984,0.002629119,0.0002019356,0.004164359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02131069,"threshold_uncertainty_score":0.0423733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2996905840769435,"score_gpt":0.2462559554714744,"score_spread":0.05343462860546913,"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."}}