{"id":"W4245677217","doi":"10.32920/ryerson.14662017","title":"Reducing linear thermal bridging in passive house details","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Sciencetech (Canada); University of Toronto","funders":"","keywords":"Bridging (networking); Thermal; Passive house; Computer science; Process engineering; Environmental science; Process (computing); Materials science; Value (mathematics); Efficient energy use; Architectural engineering; Nuclear engineering; Mechanical engineering; Engineering; Thermodynamics; Physics; Electrical engineering","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":[0.000195596,0.0004745846,0.0002610551,0.000269811,0.0001919378,0.0003926037,0.0003373321,0.0001850589,0.002334989],"category_scores_gemma":[0.0004731764,0.0002370718,0.0003326515,0.0002424167,0.0002260252,0.0005601472,0.0004590382,0.000284995,0.0002720991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002344767,"about_ca_system_score_gemma":0.0001921315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001080337,"about_ca_topic_score_gemma":0.002085161,"domain_scores_codex":[0.999896,0.00001320572,0.000003393486,0.00001879197,0.00003806144,0.00003056134],"domain_scores_gemma":[0.9998461,0.00004646656,0.00003421887,0.00003150105,0.00003159402,0.00001011579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003254652,0.0002070085,0.01176895,0.0005015847,0.0000622689,0.0003424388,0.0003149785,0.4115849,0.4733349,0.005954893,0.0007923341,0.09481019],"study_design_scores_gemma":[0.00006344767,0.001428497,0.03429781,0.00004497703,0.0001169574,0.0004852963,0.0004720946,0.4344306,0.5112031,0.003447853,0.01395702,0.00005232395],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9305574,0.0001924573,0.06226753,0.0000380139,0.00001765871,0.00002930027,0.00006683281,0.0002423114,0.006588565],"genre_scores_gemma":[0.9930801,0.00005798636,0.005659387,0.000007833908,0.00000219333,0.000009429351,0.00004976922,0.00003228194,0.001100987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002334989,"threshold_uncertainty_score":0.007811308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01076917191097503,"score_gpt":0.2096744139678524,"score_spread":0.1989052420568774,"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."}}