{"id":"W2969929970","doi":"10.1155/2019/8560204","title":"Impact of High-Altitude on Truck’s Climbing Speed: Case study in Qinghai-Tibet Plateau Area in China","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Truck; Altitude (triangle); Climbing; Effects of high altitude on humans; Environmental science; Meteorology; Automotive engineering; Engineering; Geography; Mathematics; Structural 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005075354,0.0004965059,0.000328045,0.0009689628,0.001890882,0.0006941953,0.0008569983,0.0006904727,0.001183111],"category_scores_gemma":[0.0006895689,0.0002301839,0.0004818516,0.001485028,0.0006590258,0.000564537,0.0006144807,0.0003437459,0.0001127448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00216587,"about_ca_system_score_gemma":0.001863514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1967577,"about_ca_topic_score_gemma":0.2679689,"domain_scores_codex":[0.9995998,0.00007227446,0.00002421122,0.00005894831,0.00009973447,0.0001450937],"domain_scores_gemma":[0.9994518,0.0001281753,0.00008512268,0.00003635189,0.0001659775,0.0001326616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003027993,0.0009479828,0.9181163,0.0002014078,0.0001279819,0.02831959,0.007109817,0.01622135,0.007840103,0.0007079859,0.0008972881,0.01920742],"study_design_scores_gemma":[0.00002917107,0.0006715178,0.954948,0.0000287183,0.0000785646,0.001312086,0.0186284,0.02160302,0.001402873,0.0002221379,0.001017542,0.00005788799],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994447,0.00001655839,0.0001132183,0.00002025074,0.000001177183,0.00001241984,0.00004417692,0.000003765908,0.0003436803],"genre_scores_gemma":[0.9993221,0.00004150605,0.0001757179,0.000008629029,0.000001745966,0.000008117207,0.00009154233,0.000001976217,0.0003486376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1967577,"threshold_uncertainty_score":0.3912249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005358351199860457,"score_gpt":0.2405315747227545,"score_spread":0.235173223522894,"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."}}