{"id":"W629668786","doi":"","title":"Fleet Stats 2011: Creeping Back to Life","year":2011,"lang":"en","type":"article","venue":"Progressive railroading","topic":"Transport and Economic Policies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Quarter (Canadian coin); Engineering; Fleet management; Rail freight transport; Business; Geography","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":[0.01089681,0.0008946046,0.001067178,0.01034782,0.001029335,0.007566868,0.002236427,0.00259578,0.0403053],"category_scores_gemma":[0.06692046,0.001621762,0.00102422,0.01886323,0.0008107797,0.008969409,0.002759269,0.006312096,0.05013424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005443843,"about_ca_system_score_gemma":0.007577104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04919132,"about_ca_topic_score_gemma":0.03992996,"domain_scores_codex":[0.98838,0.002615035,0.001477582,0.00103594,0.005327398,0.001164057],"domain_scores_gemma":[0.9532812,0.01286834,0.004424426,0.006546749,0.01997188,0.002907371],"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":[0.00004594883,0.00001137245,0.001375664,0.00009657663,0.0000147927,0.00001578749,0.00004771979,0.0004568734,0.00001930455,0.01063453,0.9716976,0.01558386],"study_design_scores_gemma":[0.00002111754,0.00001812721,0.006615067,0.0002560561,0.00001055752,0.00005239013,0.00009628156,0.0006492037,0.0001638586,0.00444419,0.9876205,0.00005250442],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.005061602,0.002810103,0.0149067,0.03622406,0.00821994,0.0001530047,0.8115906,0.0110551,0.1099789],"genre_scores_gemma":[0.02644568,0.003930836,0.01013987,0.01093448,0.002186608,0.0005467213,0.8755593,0.007488754,0.06276778],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04919132,"threshold_uncertainty_score":0.1348346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05950109602986423,"score_gpt":0.2405834811323248,"score_spread":0.1810823851024606,"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."}}