{"id":"W4397008980","doi":"10.14716/ijtech.v15i3.5265","title":"Analysis of Combined Braking Torque on The Regenerative Anti-Lock Braking System in The Quarter Electric Vehicle Model","year":2024,"lang":"en","type":"article","venue":"International Journal of Technology","topic":"Engineering Applied Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dynamic braking; Engine braking; Regenerative brake; Retarder; Anti-lock braking system; Automotive engineering; Threshold braking; Braking system; Torque; Electronic brakeforce distribution; Lock (firearm); Electric vehicle; Quarter (Canadian coin); Braking chopper; Brake; Engineering; Computer science; Mechanical engineering; Physics; Electrical engineering; Voltage","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":[0.0005418907,0.00009562433,0.0002058821,0.001771547,0.00002068606,0.00005066672,0.0006868801,0.00009368263,0.000005155151],"category_scores_gemma":[0.00005881386,0.00005953952,0.0001145652,0.001347845,0.00002966877,0.00006117654,0.00003228689,0.0006597538,0.000003092722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002235732,"about_ca_system_score_gemma":0.0000318507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008705326,"about_ca_topic_score_gemma":0.00001140335,"domain_scores_codex":[0.998948,0.00003203612,0.0003737037,0.00009055844,0.0004088675,0.000146767],"domain_scores_gemma":[0.999368,0.0002567627,0.00006955874,0.0001603876,0.0001331246,0.00001222183],"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":[0.00001290328,0.00001970096,0.0006945734,0.00002326612,0.00110271,0.00009473492,0.0003232921,0.8521255,0.06421802,0.07927852,0.0002391799,0.001867642],"study_design_scores_gemma":[0.0001204831,0.00004980295,0.0009356692,0.0001521448,0.00005529215,0.0000595844,0.0003351925,0.9791093,0.01866183,0.0004227922,0.0000420902,0.00005584044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808506,0.0004736418,0.01562729,0.002045727,0.00024234,0.00007845853,0.000004639872,0.00007921993,0.0005980675],"genre_scores_gemma":[0.9996834,0.00003314331,0.0001697114,0.00002135298,0.00006076292,0.000009925476,7.533613e-7,0.00001470746,0.000006251259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1269838,"threshold_uncertainty_score":0.2866338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01002967198787095,"score_gpt":0.2628204824816107,"score_spread":0.2527908104937397,"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."}}