{"id":"W4390951826","doi":"10.1007/s13132-023-01680-4","title":"Identifying Digital Transformation Barriers in Small and Medium-Sized Construction Enterprises: A Multi-criteria Perspective","year":2024,"lang":"en","type":"article","venue":"Journal of the Knowledge Economy","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Social Science Fund of China; National Natural Science Foundation of China","keywords":"Context (archaeology); Computer science; Relevance (law); Process (computing); Categorization; Risk analysis (engineering); Knowledge management; Process management; Management science; Business; Engineering; 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":[0.0124373,0.0007782328,0.001482179,0.005474215,0.002367808,0.01068503,0.00153627,0.002128461,0.00311365],"category_scores_gemma":[0.02932063,0.0005501912,0.00131318,0.00388398,0.002475807,0.004075472,0.003273872,0.001603817,0.0001017657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005690886,"about_ca_system_score_gemma":0.006659086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01365958,"about_ca_topic_score_gemma":0.01695361,"domain_scores_codex":[0.9921595,0.004214591,0.0003440811,0.0003942264,0.001597166,0.001290521],"domain_scores_gemma":[0.9603192,0.03331761,0.002039189,0.0003183567,0.00247777,0.001527844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003789766,0.003526928,0.1526582,0.00264531,0.001277821,0.002882272,0.01171409,0.5194258,0.01402068,0.1386033,0.001877572,0.1475782],"study_design_scores_gemma":[0.0001632241,0.001512896,0.07627857,0.0009059104,0.0005375582,0.0002755181,0.05672856,0.7476262,0.007944455,0.1032214,0.004534841,0.0002709268],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9462368,0.0003951898,0.04142366,0.0007569265,0.00002065982,0.0005248485,0.0001157771,0.00002130795,0.01050472],"genre_scores_gemma":[0.9909733,0.00008142881,0.008447191,0.00002368489,0.000003667337,0.0000797032,0.00004663345,0.000005003551,0.0003393762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01365958,"threshold_uncertainty_score":0.06577551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09407732000887291,"score_gpt":0.3987717261409994,"score_spread":0.3046944061321264,"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."}}