{"id":"W4376138748","doi":"10.3390/app13105906","title":"Predicting Maximum Effective Temperatures and Thermal Gradients for Steel I-Girder in Canadian Climate Regions","year":2023,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Fire effects on concrete materials","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Temperature gradient; Thermal; Materials science; Finite element method; Parametric statistics; Structural engineering; Meteorology; Engineering; Mathematics; Geography; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002405621,0.0005766961,0.0002082064,0.0007847475,0.0005643586,0.0004615898,0.0006115259,0.0004072174,0.0004370177],"category_scores_gemma":[0.0005216335,0.0003292968,0.0005079844,0.0005075727,0.000386094,0.0002121518,0.0002339274,0.0002412164,0.0001102726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003694446,"about_ca_system_score_gemma":0.003202224,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7472749,"about_ca_topic_score_gemma":0.8747675,"domain_scores_codex":[0.9998536,0.000009222292,0.000004968676,0.00003574729,0.00005350166,0.00004289985],"domain_scores_gemma":[0.9998715,0.00002967612,0.00001629001,0.000008357923,0.00006307451,0.00001112705],"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":[0.00009369574,0.00004231422,0.07935034,0.00005403984,0.00002615265,0.0001446171,0.0002019927,0.8832543,0.0209284,0.0007000898,0.0003118649,0.01489216],"study_design_scores_gemma":[0.0000112965,0.0000369815,0.139266,0.00001409976,0.00003167264,0.00004979467,0.0002727975,0.8467235,0.01263202,0.0001860254,0.0007373623,0.00003850282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939441,0.0000356048,0.003663954,0.00001090495,0.000001995108,0.00001326653,0.0002923811,0.00005913347,0.001978625],"genre_scores_gemma":[0.9967721,0.00003510928,0.002605478,0.000002576799,3.565142e-7,0.000007674677,0.0002375943,0.00001171638,0.0003273748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2527251,"threshold_uncertainty_score":0.5084269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008704291758654809,"score_gpt":0.2274669962695972,"score_spread":0.2187627045109424,"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."}}