{"id":"W4384822396","doi":"10.3390/engproc2023036051","title":"A Framework for Smart Pavements in Canada","year":2023,"lang":"en","type":"article","venue":"","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Waterloo","funders":"","keywords":"Reliability (semiconductor); Durability; Computer science; Compromise; Pavement engineering; Task (project management); Empirical research; Pavement management; Data collection; Transport engineering; Engineering; Risk analysis (engineering); Systems engineering; Business; Asphalt","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":[0.0009556732,0.0006526047,0.0004057559,0.001831721,0.003468635,0.00491635,0.002515129,0.001455393,0.009171395],"category_scores_gemma":[0.002134575,0.0003951894,0.0009708887,0.00259914,0.003373528,0.002182619,0.003131241,0.001195498,0.0008031658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03841513,"about_ca_system_score_gemma":0.040134,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9493043,"about_ca_topic_score_gemma":0.9543949,"domain_scores_codex":[0.9990095,0.0001757,0.00004651544,0.0001888507,0.0003664285,0.0002128729],"domain_scores_gemma":[0.9992367,0.00009220774,0.00004077736,0.00005959406,0.0004497888,0.0001209249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001485407,0.00002247486,0.002157559,0.00004690511,0.0000159993,0.0002692292,0.0006244646,0.09018543,0.0002918181,0.8865108,0.005459043,0.01440137],"study_design_scores_gemma":[0.00002730416,0.00002929138,0.004104022,0.0001907506,0.00004575203,0.0001757494,0.002750884,0.5269514,0.0004538752,0.2343883,0.2307913,0.00009139264],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05779734,0.001934564,0.5087429,0.01149502,0.000357624,0.001121384,0.005644855,0.001095939,0.4118104],"genre_scores_gemma":[0.616225,0.001869514,0.3233607,0.0004256561,0.00006143595,0.000552175,0.00185667,0.0001323264,0.05551644],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05069572,"threshold_uncertainty_score":0.2787226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01092854579185617,"score_gpt":0.2242864571959553,"score_spread":0.2133579114040991,"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."}}