{"id":"W1529431045","doi":"10.1007/978-3-642-03364-3_42","title":"Construction Knowledge Transfer through Interactive Visualization","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"BIM and Construction Integration","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Laptop; Variety (cybernetics); Computer science; Knowledge transfer; Entertainment; Visualization; Demographics; Installation; Workforce; Population; Knowledge management; Data science; Artificial intelligence","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":[0.0008474176,0.0006736173,0.0005261053,0.001331048,0.0004675604,0.00295883,0.001359594,0.0008642059,0.01957059],"category_scores_gemma":[0.003633519,0.0005247679,0.0005654222,0.001466423,0.001000276,0.005654726,0.003578451,0.001066162,0.002360154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004898996,"about_ca_system_score_gemma":0.0004697022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001439185,"about_ca_topic_score_gemma":0.001334668,"domain_scores_codex":[0.9995638,0.0001006314,0.00002196646,0.00008031396,0.0001965728,0.00003675566],"domain_scores_gemma":[0.9986541,0.0008755346,0.00003105936,0.0002957148,0.0001194061,0.0000241187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001212967,0.0001213029,0.0004790702,0.0004496574,0.00004797777,0.0002483235,0.004080778,0.02996847,0.02224165,0.1307466,0.01163521,0.7998596],"study_design_scores_gemma":[0.00007254198,0.0001231326,0.002360245,0.000419041,0.0001442553,0.0007928768,0.002746841,0.331308,0.07421087,0.4157914,0.1719295,0.0001013285],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02158404,0.0005463879,0.9047331,0.0004191257,0.00006416232,0.00006296411,0.0001668845,0.004554818,0.06786861],"genre_scores_gemma":[0.5235533,0.001872594,0.4291023,0.0001084245,0.00005133406,0.000232904,0.0008559527,0.001183458,0.04303991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01957059,"threshold_uncertainty_score":0.06547016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111291631263715,"score_gpt":0.2451645409763001,"score_spread":0.234051624663663,"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."}}