{"id":"W4200124175","doi":"10.1088/1742-6596/2069/1/012091","title":"Component sequence and thermal mass effects on the transient thermal performance of concrete walls","year":2021,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Thermal mass; Transient (computer programming); Thermal; Dynamic insulation; Multiphysics; Thermal resistance; Building envelope; Thermal bridge; Energy (signal processing); Thermal insulation; Thermal diffusivity; Materials science; Environmental science; Envelope (radar); Structural engineering; Mechanics; Nuclear engineering; Layer (electronics); Engineering; Composite material; Meteorology; Aerospace engineering; Computer science; Vacuum insulated panel; Thermodynamics; Physics; Finite element method","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002755012,0.0004085162,0.0002601465,0.0003374286,0.0002642311,0.0005642072,0.0002164212,0.0002295833,0.001540071],"category_scores_gemma":[0.0007023648,0.0001711947,0.0003067764,0.0003076486,0.0003760925,0.0002462662,0.0002272963,0.0002417953,0.0001854944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003151024,"about_ca_system_score_gemma":0.00026631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002408934,"about_ca_topic_score_gemma":0.002451678,"domain_scores_codex":[0.9998966,0.00001929581,0.00000556847,0.00001653303,0.00002847271,0.00003344018],"domain_scores_gemma":[0.9996295,0.0001992932,0.00005420397,0.00003051716,0.00006021868,0.0000262929],"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":[0.0008040634,0.0001144702,0.01065748,0.0001286238,0.00003612896,0.0003439143,0.000161155,0.7212474,0.2543245,0.0008037969,0.0001634136,0.01121503],"study_design_scores_gemma":[0.00003055875,0.001134199,0.03257878,0.00003556621,0.00007796376,0.0001187402,0.0002952753,0.714893,0.2498018,0.0003526132,0.0006360193,0.00004546424],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961897,0.00006471605,0.002667874,0.000006951483,0.000007104947,0.000004834357,0.00003499646,0.00003110813,0.0009927729],"genre_scores_gemma":[0.9995261,0.00001666693,0.000289341,0.000001019168,4.989612e-7,0.000002155238,0.00001716277,0.000004879788,0.0001422872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002408934,"threshold_uncertainty_score":0.005152047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01373987326043882,"score_gpt":0.191978724779245,"score_spread":0.1782388515188061,"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."}}