{"id":"W3130493259","doi":"10.1007/s00382-021-05644-9","title":"Ensemble projection of city-level temperature extremes with stepwise cluster analysis","year":2021,"lang":"en","type":"article","venue":"Climate Dynamics","topic":"Climate variability and models","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Prince Edward Island; University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Downscaling; Environmental science; Climatology; Climate change; Representative Concentration Pathways; GCM transcription factors; Baseline (sea); Cluster (spacecraft); Global warming; Scale (ratio); Ensemble average; Climate model; Mean radiant temperature; Greenhouse gas; General Circulation Model; Geography; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002595337,0.0001502011,0.000272522,0.00006183483,0.0001153087,0.00003944215,0.0001191099,0.000114847,0.0005974657],"category_scores_gemma":[0.00002791795,0.0001250268,0.0001198799,0.0009481764,0.0001285696,0.0001972274,0.0001917832,0.0001353888,0.00001662188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001872828,"about_ca_system_score_gemma":0.00002365458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001607695,"about_ca_topic_score_gemma":0.007280163,"domain_scores_codex":[0.9987426,0.00007097224,0.0002603699,0.0003971119,0.0002606084,0.0002683195],"domain_scores_gemma":[0.9992854,0.00005417031,0.0001115099,0.0004388618,0.00004705164,0.00006298177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000239398,0.0008221715,0.8670403,0.0002292443,0.0003823054,0.00003259052,0.001515948,0.09800029,0.02807933,0.00122821,0.0001942014,0.002235975],"study_design_scores_gemma":[0.001120342,0.0001800929,0.1664309,0.00006543212,0.001107757,0.00004785292,0.001662427,0.82388,0.003817168,0.0007508904,0.000316079,0.0006210404],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878106,0.00001086098,0.004822761,0.0002291424,0.00005680275,0.0001717247,0.0001809501,0.00003460999,0.006682554],"genre_scores_gemma":[0.9933322,0.00007705465,0.005364351,0.0001253191,0.00001041369,0.00001410443,0.0002325661,0.00001485003,0.0008291538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7258797,"threshold_uncertainty_score":0.654183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01925324890803727,"score_gpt":0.2380529821806052,"score_spread":0.2187997332725679,"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."}}