{"id":"W2808857317","doi":"10.1049/cp.2018.0050","title":"Low Adhesion Braking Dynamic Optimisation for Rolling Stock (LABRADOR) Simulation Model","year":2018,"lang":"en","type":"article","venue":"","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Train; Braking system; Brake; MATLAB; Computer science; Disc brake; Automotive engineering; Vehicle dynamics; Engineering; Simulation; Control 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001085299,0.0001537843,0.0001220175,0.0001066423,0.00009055102,0.0000437922,0.00008288639,0.0001106976,0.00001081223],"category_scores_gemma":[0.00003104201,0.0001625475,0.00005645838,0.0001108819,0.00001163264,0.0002140158,0.00001073627,0.00007410366,0.00001474094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001201261,"about_ca_system_score_gemma":0.0000111658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002256071,"about_ca_topic_score_gemma":0.00001184747,"domain_scores_codex":[0.9992754,0.000003708919,0.0002088246,0.0001672227,0.0001099286,0.0002348713],"domain_scores_gemma":[0.9996039,0.00007081818,0.00002390294,0.0001766973,0.00007304148,0.00005160278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009576172,0.000006476711,0.000006890116,0.00005473743,0.00001208563,9.141311e-8,0.0001592295,0.9787359,0.008059325,0.0001776659,0.0000285339,0.01274953],"study_design_scores_gemma":[0.0002835505,0.00004175076,0.000062238,0.00003738895,0.00001361374,6.286382e-7,0.00001138758,0.9966405,0.002305127,0.0003458814,0.00005147543,0.000206448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2354696,0.00002275838,0.7627303,0.000008829466,0.0002507645,0.0001876429,0.000007233612,0.000655186,0.0006677092],"genre_scores_gemma":[0.9272867,0.000006191518,0.07214644,0.00001740752,0.0001186422,0.00001883186,0.00003982781,0.00006214771,0.0003037398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6918172,"threshold_uncertainty_score":0.6628496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01345551272120761,"score_gpt":0.2467556070137289,"score_spread":0.2333000942925213,"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."}}