{"id":"W3178654013","doi":"10.3390/buildings11070291","title":"A Taxonomy of Sources of Waste in BIM Information Flows","year":2021,"lang":"en","type":"article","venue":"Buildings","topic":"BIM and Construction Integration","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Building information modeling; Taxonomy (biology); Design science research; Computer science; Process (computing); Work (physics); Data science; Construction engineering; Systems engineering; Process management; Management science; Engineering; Knowledge management; Information system; Compatibility (geochemistry)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003451229,0.00003448698,0.00007058275,0.00008452699,0.000004925149,0.000006339019,0.00002788812,0.00003191196,0.00004322291],"category_scores_gemma":[0.00001560565,0.00003583941,0.00002218805,0.0001652168,0.000009372234,0.0001934953,0.000006632059,0.0000384819,0.000002602427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001263996,"about_ca_system_score_gemma":0.00001357776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002660314,"about_ca_topic_score_gemma":0.00001853525,"domain_scores_codex":[0.9996969,0.000003630352,0.0001810853,0.0000260596,0.00004894934,0.00004333641],"domain_scores_gemma":[0.999854,0.000009214029,0.00003180396,0.00005090475,0.00004503532,0.000008999678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003251137,0.00004015552,0.03491538,0.001032284,0.0000926341,0.000002695877,0.007684732,0.1159819,0.2045646,0.06797788,0.001212175,0.5664631],"study_design_scores_gemma":[0.0005311552,0.00001895009,0.002072554,0.0001752976,0.00001057841,0.00001719311,0.003987972,0.04736898,0.8784525,0.0004909348,0.06672762,0.0001462606],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880093,0.0001004511,0.00899976,0.00001308793,0.0001040111,0.00003786806,0.000003204915,0.00001943715,0.002712924],"genre_scores_gemma":[0.9967114,0.000016877,0.003228812,0.000006368903,0.00001263445,0.000008993135,0.000003171274,0.000002300223,0.000009430475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6738879,"threshold_uncertainty_score":0.1461489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007247556843511987,"score_gpt":0.1760878717404917,"score_spread":0.1688403148969797,"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."}}