{"id":"W3123138904","doi":"10.1155/2021/8833058","title":"Digital Twins and Road Construction Using Secondary Raw Materials","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"BIM and Construction Integration","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020 Framework Programme; European Commission","keywords":"Demolition; Raw material; Construction engineering; Work (physics); Road construction; Parallels; Engineering; Civil engineering; Computer science; Transport engineering; Operations management; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003286025,0.0000733179,0.0001331226,0.00006520723,0.00003181523,0.00005071077,0.00001771921,0.00004675216,0.00006990832],"category_scores_gemma":[0.000005697872,0.00007408668,0.00003737958,0.00008625575,0.00002678542,0.0008929352,5.155068e-7,0.0000970701,6.034641e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002754511,"about_ca_system_score_gemma":0.00003873572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.647926e-7,"about_ca_topic_score_gemma":0.000008640305,"domain_scores_codex":[0.9994305,0.000007169237,0.0003461572,0.0000577652,0.00009469061,0.00006369975],"domain_scores_gemma":[0.9996618,0.000007995731,0.0001093307,0.00003751888,0.0001455272,0.00003781264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004758705,0.00001033408,0.0008252244,0.00006516766,0.00006122918,0.00003343678,0.0004522831,0.03714192,0.6811909,0.000811709,0.00001138045,0.2793488],"study_design_scores_gemma":[0.003080351,0.0001319726,0.2142795,0.0003710102,0.0001934605,0.002376502,0.005366815,0.000843704,0.7649209,0.004461217,0.003488101,0.0004864534],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803678,0.0004155518,0.01778914,0.00001622654,0.001148303,0.00002895034,0.00002857981,0.00002216576,0.0001832935],"genre_scores_gemma":[0.9920285,0.0001778792,0.007615541,0.000008811246,0.0001146687,5.076044e-7,0.0000326903,0.00001054729,0.00001087637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2788624,"threshold_uncertainty_score":0.3021167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005829596639802246,"score_gpt":0.2094027296301792,"score_spread":0.203573132990377,"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."}}