{"id":"W4400093875","doi":"10.5194/gmd-17-5023-2024","title":"WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model","year":2024,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Mesoscale meteorology; Environmental science; Meteorology; Microscale chemistry; Wind speed; Weather Research and Forecasting Model; MM5; Atmospheric sciences; Relative humidity; Thermal comfort; Downscaling; Climatology; Geography; Precipitation; Geology; Mathematics","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":[0.0003609303,0.0006357727,0.0006502486,0.0003316205,0.0004072321,0.0009648592,0.001222887,0.001403316,0.002197365],"category_scores_gemma":[0.0009487813,0.0003761038,0.0009249088,0.0004824651,0.0004411859,0.0005860525,0.0006997995,0.001233461,0.0002232354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008316257,"about_ca_system_score_gemma":0.0009135933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04392683,"about_ca_topic_score_gemma":0.02678058,"domain_scores_codex":[0.9998838,0.0000308679,0.000006154828,0.00002886497,0.00002472154,0.000025654],"domain_scores_gemma":[0.9996283,0.0001470505,0.00004412339,0.00005275045,0.00006276189,0.0000649372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002567159,0.00005043895,0.002458393,0.00001488418,0.00002827232,0.00003170732,0.00001618804,0.9939625,0.000795647,0.0006085982,0.0003640325,0.001643648],"study_design_scores_gemma":[0.000009044941,0.000006497286,0.0004524259,0.000001155209,0.000002321139,0.000001731807,0.000004316279,0.9991928,0.00007221073,0.000129707,0.000124797,0.000003040629],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8645868,0.0002862327,0.1146815,0.0007014722,0.0001747769,0.0001560335,0.003476493,0.002597168,0.01333954],"genre_scores_gemma":[0.9721301,0.00006301829,0.02498693,0.00006845935,0.00002340823,0.00009729999,0.001232889,0.0001336387,0.001264383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04392683,"threshold_uncertainty_score":0.08734232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01335973732311016,"score_gpt":0.2198570298299153,"score_spread":0.2064972925068052,"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."}}