{"id":"W6893065418","doi":"10.5281/zenodo.14524342","title":"Climate Solutions Explorer - hazard, impacts and exposure data","year":2024,"lang":"en","type":"dataset","venue":"IIASA PURE (International Institute of Applied Systems Analysis)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"European Commission","keywords":"Climate change; Precipitation; Climate model; Climate extremes; Global warming; NetCDF; Downscaling; Population; Greenhouse gas","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002350956,0.001186747,0.002333308,0.003510345,0.0003159618,0.0009975208,0.003693599,0.0008341816,0.000302693],"category_scores_gemma":[0.0001877321,0.001094787,0.0006307236,0.002139957,0.0005563598,0.001167486,0.003179335,0.001095547,0.005275661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004806606,"about_ca_system_score_gemma":0.000450996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00123455,"about_ca_topic_score_gemma":0.007473323,"domain_scores_codex":[0.9916065,0.0001104947,0.002466695,0.002355634,0.002525452,0.0009352127],"domain_scores_gemma":[0.9929187,0.0001312984,0.00185097,0.004084176,0.0005691067,0.0004457085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001538534,0.0002407907,0.00004195119,0.001234994,0.0193041,0.0001620496,0.00009773367,0.007918705,0.0002619874,0.007744138,0.9627848,0.00005491614],"study_design_scores_gemma":[0.0007051554,0.0000326924,0.0001100124,0.0008905928,0.01218319,0.00007354147,0.0003271348,0.007088867,0.000007424599,0.0001032302,0.9775355,0.0009426363],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000615707,0.004282478,0.0001559329,0.0001523351,0.004464865,0.001007225,0.9871309,0.0002158685,0.001974682],"genre_scores_gemma":[0.05261462,0.002371325,0.0001793779,0.00005035422,0.001522525,0.0002565676,0.9427452,0.0001417229,0.0001183191],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05199891,"threshold_uncertainty_score":0.9991502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05453544799455452,"score_gpt":0.3066609136327502,"score_spread":0.2521254656381957,"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."}}