{"id":"W3148645634","doi":"10.1177/03611981211003572","title":"Performance Evaluation of Different Insulating Materials using Field Temperature and Moisture Data","year":2021,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Subgrade; Polystyrene; Moisture; Materials science; Frost (temperature); Geotechnical engineering; Composite material; Penetration (warfare); Water content; Thermal insulation; Polyethylene; Layer (electronics); Geology; Polymer; Engineering","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":[0.0005757773,0.0007050924,0.0005245246,0.0008414155,0.0004596317,0.0005350964,0.0006662831,0.0002955063,0.0004279659],"category_scores_gemma":[0.0005200271,0.0001873755,0.0003294927,0.0006136888,0.0002843821,0.0004242013,0.0002259052,0.0002418391,0.000192041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009837694,"about_ca_system_score_gemma":0.0004819586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0255935,"about_ca_topic_score_gemma":0.07792781,"domain_scores_codex":[0.9995943,0.00003709212,0.00002205694,0.00009056713,0.0001882432,0.00006772214],"domain_scores_gemma":[0.9994534,0.0000798137,0.00008962211,0.00004129662,0.0002741808,0.00006175164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006923184,0.0002198693,0.03558503,0.0001530689,0.00004919342,0.0001373673,0.0001835753,0.004015703,0.9412133,0.00002829276,0.0000365436,0.01768585],"study_design_scores_gemma":[0.0000131902,0.003629104,0.1800095,0.0000131505,0.0001522889,0.0001289466,0.0004201898,0.005233103,0.8093724,0.00002155605,0.0009753647,0.00003123165],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990134,0.00008871165,0.0006027433,0.000002359693,0.000002589729,0.000009827932,0.00006726229,0.00001621995,0.0001968663],"genre_scores_gemma":[0.9960669,0.0001788108,0.002530822,0.000005177132,0.000002031462,0.00000788514,0.0003355625,0.00001704401,0.0008558871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0255935,"threshold_uncertainty_score":0.05088902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1238177030613024,"score_gpt":0.3827093331873292,"score_spread":0.2588916301260268,"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."}}