{"id":"W2554140922","doi":"10.47893/ijcct.2010.1004","title":"Intelligent Transport Systems in Commercial Vehicle Operations","year":2010,"lang":"en","type":"article","venue":"International Journal of Computer and Communication Technology","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Software deployment; Intelligent transportation system; Transport engineering; Advanced Traffic Management System; Information technology; Information exchange; Information system; Engineering; Engineering management; Telecommunications; Computer security; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007304407,0.0004082252,0.0002868617,0.00107334,0.00108105,0.005049018,0.0006090931,0.001990705,0.007547724],"category_scores_gemma":[0.001564264,0.0002061835,0.0003449678,0.00142702,0.002304688,0.003720531,0.001283641,0.001329788,0.001541341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003184086,"about_ca_system_score_gemma":0.001691191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009851875,"about_ca_topic_score_gemma":0.004093799,"domain_scores_codex":[0.9993057,0.0002718104,0.00004162746,0.000113698,0.000175121,0.00009203049],"domain_scores_gemma":[0.9994203,0.000238949,0.00007444852,0.00004772786,0.0001706861,0.00004789415],"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":[0.0000158915,0.00002429522,0.0007081793,0.0001218615,0.000008048489,0.0003066713,0.0007084251,0.01252063,0.0003935928,0.919088,0.01400293,0.05210138],"study_design_scores_gemma":[0.00001385266,0.00007817322,0.001528329,0.0003986771,0.00002073032,0.0003746811,0.00170568,0.0427968,0.0007811229,0.4616587,0.4905944,0.00004885096],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0284593,0.07783284,0.1675868,0.03245535,0.003083337,0.0001266547,0.0002223037,0.0005431941,0.6896902],"genre_scores_gemma":[0.7919583,0.04904882,0.02447677,0.00232777,0.002688328,0.000163418,0.0002890361,0.0001194049,0.1289281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009851875,"threshold_uncertainty_score":0.02524972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006880274760148948,"score_gpt":0.2386106687609557,"score_spread":0.2317303940008067,"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."}}