{"id":"W637503807","doi":"","title":"DEALING WITH M/W UNDER HEAVY HAUL","year":2000,"lang":"en","type":"article","venue":"Railway track and structures","topic":"Transport and Economic Policies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pound (networking); Track (disk drive); Engineering; Axle; Transport engineering; Axle load; Freight trains; Train; Computer science; Geography; Mechanical engineering","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":[0.003991429,0.0002788826,0.0002380652,0.001092464,0.003262192,0.003771556,0.001059702,0.002328774,0.007898977],"category_scores_gemma":[0.009534079,0.0002120137,0.0002927565,0.001391473,0.00219159,0.003581145,0.001947235,0.001976299,0.0009726792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001664577,"about_ca_system_score_gemma":0.003036828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008144029,"about_ca_topic_score_gemma":0.01109699,"domain_scores_codex":[0.9958692,0.0007147195,0.0002074188,0.0003069272,0.002024657,0.0008769688],"domain_scores_gemma":[0.9952886,0.001146556,0.001212848,0.0009569062,0.0009465096,0.0004487056],"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":[0.0001702369,0.0001174051,0.02424042,0.0002143498,0.00004710722,0.002690241,0.002470591,0.006439211,0.007037797,0.4740263,0.09579226,0.386754],"study_design_scores_gemma":[0.00002184937,0.0002917384,0.03656362,0.0004016375,0.00004557363,0.003229262,0.008991212,0.0164827,0.01090565,0.1922157,0.7307504,0.0001005637],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.3437554,0.005639492,0.05351989,0.05708533,0.001934444,0.0002516649,0.0003099421,0.000689048,0.5368147],"genre_scores_gemma":[0.9068466,0.00272505,0.008707424,0.004998067,0.001303995,0.00007193641,0.00009909564,0.00009891587,0.07514885],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.008144029,"threshold_uncertainty_score":0.02642477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01052728349892077,"score_gpt":0.1958867747822539,"score_spread":0.1853594912833331,"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."}}