{"id":"W4414948238","doi":"10.3390/infrastructures10100266","title":"Digital Integration in Construction: A Case Study on Common Data Environment Implementation for a Metro Line Project","year":2025,"lang":"en","type":"article","venue":"Infrastructures","topic":"BIM and Construction Integration","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Workflow; Software deployment; Automation; Consistency (knowledge bases); Stakeholder; Cloud computing; Field (mathematics); Data integration; System integration","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":[0.01046833,0.0005088278,0.0004728161,0.001772336,0.009364641,0.003673388,0.001857079,0.002230887,0.002172051],"category_scores_gemma":[0.01560838,0.0005463658,0.0003771357,0.002613396,0.005398357,0.002752914,0.004880347,0.002210294,0.0003961388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006944173,"about_ca_system_score_gemma":0.007703323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01523379,"about_ca_topic_score_gemma":0.04167985,"domain_scores_codex":[0.9881015,0.007309796,0.0003608257,0.0008637252,0.001961785,0.001402351],"domain_scores_gemma":[0.9869332,0.006636124,0.001218593,0.001780357,0.001870211,0.001561419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000518375,0.005836044,0.1079151,0.0008017172,0.00008382495,0.03417923,0.6132485,0.01059552,0.01325626,0.02061704,0.004412175,0.1885362],"study_design_scores_gemma":[0.000104151,0.003131808,0.06593645,0.0004461877,0.00005567448,0.005734539,0.8032739,0.01141801,0.01015014,0.003906216,0.0957041,0.000138847],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851091,0.00006287692,0.006046956,0.0006266402,0.000010085,0.0002980107,0.00003924289,0.00003721748,0.007769859],"genre_scores_gemma":[0.9873918,0.0001194237,0.009306868,0.0001187912,0.000007265735,0.0001847831,0.00005416794,0.00003423243,0.002782544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01523379,"threshold_uncertainty_score":0.05536252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02646416595865115,"score_gpt":0.3243231896595297,"score_spread":0.2978590237008785,"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."}}