{"id":"W7154970715","doi":"10.66408/sasbe.2025.2702","title":"Enabling Circularity through Dynamic Material Passports: A Framework Integrating Digital Twin Technologies and Data Governance in the Built Environment","year":2025,"lang":"","type":"article","venue":"Proceedings of Smart and Sustainable Built Environment Conference Series","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Sustainability; Key (lock); Built environment; Building information modeling; Reuse; Scalability; Stakeholder; Resource (disambiguation)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.011226,0.0007825702,0.0006363522,0.003456551,0.003436005,0.01263913,0.002701889,0.003373503,0.003000526],"category_scores_gemma":[0.01156869,0.0007487023,0.001868765,0.003175478,0.01434623,0.01751173,0.01015228,0.003857096,0.0006881282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004809314,"about_ca_system_score_gemma":0.01183984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009476452,"about_ca_topic_score_gemma":0.008593269,"domain_scores_codex":[0.9920856,0.003761984,0.0007068248,0.001191409,0.001535818,0.0007183148],"domain_scores_gemma":[0.9919682,0.002930044,0.0008117,0.002586193,0.0009775148,0.0007264016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005013362,0.00001359668,0.0002006469,0.00002712792,0.000006020075,0.00009616416,0.0004267347,0.004183925,0.0001486192,0.9877691,0.0004077106,0.006715499],"study_design_scores_gemma":[0.00001945752,0.00003656558,0.0002329006,0.0002765317,0.00004157355,0.0002210265,0.001007569,0.04335171,0.001145048,0.8696828,0.08393643,0.00004843181],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00767945,0.0004442143,0.9533222,0.00364585,0.0001089573,0.0002601687,0.0001213392,0.0003456659,0.0340721],"genre_scores_gemma":[0.3630751,0.001146693,0.6265435,0.0006652257,0.00011595,0.0005921093,0.0003205134,0.0001417158,0.007399242],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01263913,"threshold_uncertainty_score":0.05936944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187067527726567,"score_gpt":0.2236857705431852,"score_spread":0.2118150952659195,"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."}}