{"id":"W2980059660","doi":"","title":"A Framework for Improving Business and Technical Operations within Timber Frame Self-Build Housing Sector by Applying an Integrated VR/AR and BIM Approach","year":2019,"lang":"en","type":"article","venue":"TeesRep (Teesside University)","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Frame (networking); Building information modeling; Public housing; Computer science; Virtual reality; Housing industry; Business; Architectural engineering; Engineering; Operations management; Human–computer interaction; Civil engineering; Mechanical engineering","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":[0.01932066,0.001799541,0.0005888023,0.006648415,0.003953326,0.01721274,0.005159861,0.006541543,0.005711483],"category_scores_gemma":[0.006968829,0.001015703,0.001925568,0.003615776,0.01005676,0.01311087,0.01516414,0.004104402,0.003315647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008249542,"about_ca_system_score_gemma":0.02674627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02178729,"about_ca_topic_score_gemma":0.02309082,"domain_scores_codex":[0.9860511,0.00678246,0.001027481,0.001256778,0.00292921,0.001952913],"domain_scores_gemma":[0.9943194,0.001414941,0.0005705048,0.000678486,0.001631133,0.001385471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002389143,0.0003539808,0.001933141,0.0005736556,0.00002539022,0.0008949803,0.007670617,0.008372639,0.002416607,0.8883349,0.007837265,0.08156297],"study_design_scores_gemma":[0.0000589909,0.0003748072,0.003481794,0.003314702,0.00007590968,0.001339079,0.02626598,0.04054648,0.002841613,0.3228425,0.5986767,0.000181336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0130046,0.002796015,0.8053057,0.02067185,0.0004202684,0.002047751,0.0002064634,0.001932951,0.1536144],"genre_scores_gemma":[0.1162451,0.00196949,0.8633168,0.0009259197,0.00007376856,0.0009847212,0.0003707815,0.0001775741,0.01593568],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02178729,"threshold_uncertainty_score":0.1021786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01552498317173105,"score_gpt":0.2341756904140873,"score_spread":0.2186507072423562,"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."}}