{"id":"W561945916","doi":"","title":"Railroads Continue Big Spending on M/W","year":2007,"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":"Track (disk drive); Freight trains; Engineering; Transport engineering; Rail transportation; Ballast; Chart; Geography; Archaeology; Electrical engineering; Train; Statistics","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":[0.0002354901,0.0002793246,0.0001508704,0.001008152,0.001273553,0.001642434,0.0003145912,0.0005091577,0.03145649],"category_scores_gemma":[0.0006245197,0.0001340152,0.0003061295,0.002078245,0.0002769162,0.0008883224,0.0009669012,0.00073867,0.0100304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001453176,"about_ca_system_score_gemma":0.00340099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0927726,"about_ca_topic_score_gemma":0.1779234,"domain_scores_codex":[0.9996112,0.00001377727,0.000009980798,0.00004527943,0.0001558586,0.0001639367],"domain_scores_gemma":[0.9993694,0.00003447179,0.00009282237,0.00005101169,0.000274989,0.0001773315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001268797,0.0001109754,0.08574766,0.0002220802,0.00003962931,0.0001414991,0.0009264819,0.0007235959,0.002526463,0.02003466,0.5151414,0.3742586],"study_design_scores_gemma":[0.000007710289,0.0000992179,0.1333686,0.00007580945,0.00002065349,0.0001246977,0.001645789,0.0002499276,0.0009837464,0.0005481881,0.8628616,0.00001395788],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.485422,0.003700316,0.002300832,0.02016181,0.0009010379,0.00007019482,0.01851744,0.00261615,0.4663102],"genre_scores_gemma":[0.5480594,0.005259764,0.002754767,0.003502759,0.0002318768,0.00005606277,0.02250538,0.0004485276,0.4171814],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0927726,"threshold_uncertainty_score":0.1844652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01820268724739919,"score_gpt":0.224660911884441,"score_spread":0.2064582246370419,"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."}}