{"id":"W2403559689","doi":"","title":"From Risk to Opportunity 2008: Insurer Responses to Climate Change","year":2007,"lang":"en","type":"article","venue":"","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Actuarial science; Business; Economics; Risk analysis (engineering)","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":[0.001929178,0.0001201695,0.0001000428,0.0003529674,0.00138556,0.002275987,0.0005078236,0.002047667,0.01200546],"category_scores_gemma":[0.008189018,0.00009245569,0.0002110345,0.0002908937,0.0003112567,0.001059212,0.001820222,0.00173436,0.0009879938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002465979,"about_ca_system_score_gemma":0.002099956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03132696,"about_ca_topic_score_gemma":0.06725849,"domain_scores_codex":[0.9990165,0.0002002797,0.00002884871,0.00005147216,0.0003806627,0.0003223078],"domain_scores_gemma":[0.9981199,0.0004561224,0.0003998976,0.00007588965,0.0003578917,0.0005903101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0007543071,0.0005931523,0.2219897,0.00008367185,0.0000706909,0.001074415,0.01064441,0.002251393,0.001581245,0.03000067,0.5845596,0.1463968],"study_design_scores_gemma":[0.00009973719,0.0003721494,0.578936,0.0001872581,0.00008838534,0.0003248656,0.03265265,0.01014153,0.002060603,0.009886826,0.365176,0.00007393301],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6772612,0.001872418,0.0007811938,0.1478431,0.0006762446,0.0001031489,0.002011854,0.0002009157,0.1692499],"genre_scores_gemma":[0.9719997,0.0006755932,0.0003097858,0.004683736,0.0002027684,0.00002832194,0.0005606956,0.00001914057,0.02152028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03132696,"threshold_uncertainty_score":0.06228924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06008773185600851,"score_gpt":0.3416145673882688,"score_spread":0.2815268355322603,"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."}}