{"id":"W2886103768","doi":"","title":"Application of the Universal Thermal Climate Index for Operational Forecasting in Canada","year":2014,"lang":"en","type":"article","venue":"20th International Congress of Biometeorology (28 September–2 October 2014)","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Index (typography); Climatology; Meteorology; Climate change; Environmental science; Computer science; Econometrics; Economics; Geography; Geology","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":[0.00110936,0.0004326793,0.000427226,0.001524699,0.001326674,0.001922206,0.001112692,0.0003270753,0.002164826],"category_scores_gemma":[0.003634108,0.0002100288,0.0003800345,0.003433372,0.0002925497,0.0006274873,0.0004967859,0.0005939577,0.0002034402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0274355,"about_ca_system_score_gemma":0.03757678,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9966288,"about_ca_topic_score_gemma":0.9961742,"domain_scores_codex":[0.9995446,0.0000560623,0.00003310816,0.00007973563,0.000181984,0.0001045504],"domain_scores_gemma":[0.9982376,0.0001983364,0.00006180359,0.00004604976,0.001280089,0.0001761813],"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":[0.0004337373,0.0002001521,0.3137926,0.000209612,0.0002248728,0.0002852161,0.0005935527,0.399747,0.001350546,0.009492786,0.03872033,0.2349497],"study_design_scores_gemma":[0.00004331665,0.00003105355,0.1517287,0.00005849133,0.00007437959,0.00003035828,0.0009122939,0.8311774,0.0009900067,0.001105844,0.01378021,0.00006805747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9385402,0.001996509,0.01348753,0.002402111,0.0002640016,0.0001418684,0.01684424,0.0007579266,0.02556567],"genre_scores_gemma":[0.9836945,0.0005990556,0.008002479,0.00004873812,0.00001799867,0.00002070969,0.003981628,0.00004777967,0.003587243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0274355,"threshold_uncertainty_score":0.1990594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005918069464779438,"score_gpt":0.2045485534319031,"score_spread":0.1986304839671237,"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."}}