{"id":"W2034393231","doi":"10.4028/www.scientific.net/amm.300-301.1617","title":"Research on Data Reports Based on Experimentation & Test of Traffic Engineering","year":2013,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Advanced Decision-Making Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Standardization; Objectivity (philosophy); Test (biology); Data quality; Test data; Engineering; Quality (philosophy); Computer science; Reliability engineering; Systems engineering; Software engineering; Operations management","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":[0.001038563,0.000104612,0.0001658868,0.0001698871,0.00005431475,0.0001252377,0.0004523321,0.00005897111,0.00002355809],"category_scores_gemma":[0.0001531948,0.00009297008,0.000008363714,0.0001656833,0.000007841576,0.0001536526,0.0003522006,0.00006262855,0.00001411502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002285704,"about_ca_system_score_gemma":0.00002114562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006807727,"about_ca_topic_score_gemma":3.189643e-7,"domain_scores_codex":[0.9987044,0.00002369376,0.0002909083,0.0004428434,0.0003612887,0.0001768954],"domain_scores_gemma":[0.9981335,0.0003775694,0.0001179071,0.001259132,0.00006483927,0.00004704864],"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":[0.000009200661,0.00007446425,5.27972e-8,0.00001911209,0.000002385904,0.000004324435,0.00004914209,0.0004630747,0.8224911,0.1672474,0.000668749,0.00897095],"study_design_scores_gemma":[0.0001613518,0.000194966,0.00001086833,0.0001012201,0.000002099487,0.00000549437,0.000020671,0.03100231,0.9143043,0.05310423,0.0009224268,0.00017007],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08479093,0.000008550572,0.9140791,0.00007291732,0.000186725,0.0005593708,0.0000104018,0.0001699425,0.0001220616],"genre_scores_gemma":[0.7060943,0.000006855012,0.2937199,0.00004769672,0.00001847931,0.00008217056,0.00001548132,0.00001105993,0.000004009683],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6213034,"threshold_uncertainty_score":0.379121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0781241444576021,"score_gpt":0.3623432760540844,"score_spread":0.2842191315964823,"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."}}