{"id":"W2736726216","doi":"10.1177/0954409717720347","title":"Evaluating the impact of ballast undercutting on the roughness of track geometry over different subgrade conditions","year":2017,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part F Journal of Rail and Rapid Transit","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Ballast; Subgrade; Track (disk drive); Surface finish; Track geometry; Silt; Geotechnical engineering; Surface roughness; Engineering; Structural engineering; Environmental science; Geology; Materials science; Mechanical engineering; Composite material; Electrical engineering; Geomorphology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003422221,0.0002800206,0.0002676494,0.0006548439,0.0003259503,0.0006616262,0.0003057783,0.0002581838,0.0005971392],"category_scores_gemma":[0.0009249978,0.0001280078,0.0003380938,0.0007130094,0.0002519971,0.000319389,0.0002448056,0.0002369028,0.0001638486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00155198,"about_ca_system_score_gemma":0.0008812089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2316523,"about_ca_topic_score_gemma":0.4485384,"domain_scores_codex":[0.9995783,0.00002469528,0.00001864403,0.00008783722,0.0002000586,0.00009047279],"domain_scores_gemma":[0.9991027,0.0001465366,0.0001997156,0.00005606232,0.0004134551,0.00008155207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003300426,0.0001214293,0.9316653,0.00006459064,0.00009763431,0.0001862244,0.0003303796,0.008329161,0.03933075,0.00005187772,0.0001323287,0.01936033],"study_design_scores_gemma":[9.478155e-7,0.000153326,0.9948667,0.000002221121,0.00001914634,0.00002570301,0.0001916851,0.001884593,0.002671516,0.000005050788,0.0001750393,0.000004061926],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990952,0.00003194186,0.000255912,0.000002672924,0.000001133396,0.000009098134,0.0002437251,0.000006668231,0.0003536569],"genre_scores_gemma":[0.9987092,0.00004267975,0.0004029978,0.000002933021,8.824652e-7,0.000004467728,0.0004544585,0.000003780468,0.0003786571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2316523,"threshold_uncertainty_score":0.4606079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02856123574863237,"score_gpt":0.2813946967291777,"score_spread":0.2528334609805453,"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."}}