{"id":"W3212379955","doi":"10.32920/ryerson.14663043.v1","title":"Analyzing impact of sensor coupling on measurement representativeness of wall surface temperature","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Representativeness heuristic; Coupling (piping); Materiality (auditing); Embedding; Temperature measurement; Thermal; Surface (topology); Acoustics; Materials science; Computer science; Mathematics; Statistics; Physics; Composite material; Geometry; Artificial intelligence; Thermodynamics","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":[0.001130687,0.0004757772,0.000369593,0.0003688331,0.0002434273,0.0005327658,0.0003836484,0.0005762401,0.0008101102],"category_scores_gemma":[0.005584248,0.0002693713,0.0004726805,0.0004032201,0.0004226179,0.0007118084,0.0005229429,0.0004732138,0.000110854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003388439,"about_ca_system_score_gemma":0.0002674688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002961274,"about_ca_topic_score_gemma":0.001814233,"domain_scores_codex":[0.9991441,0.0002242874,0.00004721418,0.0001512612,0.0003019807,0.0001312823],"domain_scores_gemma":[0.9957458,0.003266807,0.0002800524,0.0003133398,0.0003374715,0.0000564837],"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":[0.0006576384,0.0001578412,0.01499513,0.0003440262,0.00008213692,0.0003242427,0.0002695872,0.8907111,0.06814674,0.0006683512,0.0002184402,0.02342486],"study_design_scores_gemma":[0.00001754269,0.0006132443,0.01593387,0.00002734861,0.00006093546,0.0001064725,0.0001544739,0.8933824,0.08901665,0.000237848,0.0004163905,0.00003282842],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746207,0.0001962073,0.02342164,0.00004931333,0.00002321776,0.00002414707,0.00009958137,0.0001210292,0.001444207],"genre_scores_gemma":[0.9978544,0.00003511919,0.001919301,0.000004648459,0.000001430278,0.000007725891,0.0000325607,0.00001449094,0.0001302844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002961274,"threshold_uncertainty_score":0.005979717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02748820167666812,"score_gpt":0.2703194868146989,"score_spread":0.2428312851380308,"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."}}