{"id":"W4321501942","doi":"10.32920/ryerson.14648994.v2","title":"Timber Framing Factor in Toronto Residential House Construction","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Framing (construction); Building envelope; Environmental science; Architectural engineering; Engineering; Civil engineering; Thermal; Geography; Meteorology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003313484,0.0003284966,0.0001548911,0.0005441256,0.0005573449,0.0007669404,0.0002981031,0.0001604603,0.002169173],"category_scores_gemma":[0.0008635272,0.0001337912,0.0001809172,0.0008499536,0.000401517,0.0002043348,0.0002584981,0.0001134141,0.0003156746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00407661,"about_ca_system_score_gemma":0.001212931,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2853087,"about_ca_topic_score_gemma":0.5464294,"domain_scores_codex":[0.9995071,0.00004626866,0.00001321499,0.00006176098,0.0002728067,0.00009887142],"domain_scores_gemma":[0.9997287,0.00004727069,0.00004044711,0.00002724001,0.0001265201,0.00002982246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001098211,0.0001827603,0.5057862,0.0003159031,0.00008696583,0.00176919,0.00307653,0.1809031,0.1221123,0.007580298,0.004151645,0.172937],"study_design_scores_gemma":[0.000009792701,0.0003634603,0.9136761,0.00003898517,0.00005326548,0.0003839415,0.002601092,0.02701459,0.04615607,0.000474331,0.009169038,0.00005945181],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897937,0.0001269517,0.001264685,0.000009866848,0.000003488438,0.00001361673,0.0001898441,0.00003435107,0.008563588],"genre_scores_gemma":[0.997498,0.00004232772,0.0007844464,0.00000132383,5.590446e-7,0.000003183975,0.0001478791,0.000009719901,0.001512413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7146913,"threshold_uncertainty_score":0.5672961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01442571098219847,"score_gpt":0.236854352507645,"score_spread":0.2224286415254465,"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."}}