{"id":"W3003082627","doi":"","title":"A local multi-physical approach to model braking materials","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Brake Systems and Friction Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Volume (thermodynamics); Computer science; Braking system; Automotive engineering; Materials science; Engineering; Physics; Thermodynamics; Brake","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0007830925,0.001234557,0.001814192,0.001757548,0.001100404,0.002345674,0.003482162,0.003408189,0.005370887],"category_scores_gemma":[0.001801145,0.0008796988,0.001547765,0.001091968,0.002934974,0.003146556,0.002594791,0.002676448,0.001222144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001422782,"about_ca_system_score_gemma":0.001000969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003743194,"about_ca_topic_score_gemma":0.004328811,"domain_scores_codex":[0.999593,0.0001471647,0.00002001773,0.00006870014,0.0001207207,0.00005049656],"domain_scores_gemma":[0.9992579,0.0002317521,0.0000918114,0.0001486951,0.0001675834,0.000102271],"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":[0.00003572544,0.0001080651,0.0002646248,0.0001490021,0.00005199666,0.0001566836,0.0001145222,0.6873609,0.002922564,0.3019684,0.001296725,0.005570746],"study_design_scores_gemma":[0.000008308065,0.00001118496,0.00005697764,0.000006522045,0.000006742071,0.00001660506,0.00001689489,0.9611619,0.0001238807,0.03761629,0.0009654507,0.000009297983],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04227363,0.001898548,0.9146078,0.00150327,0.0005021585,0.00009129318,0.0001674699,0.0003279518,0.03862791],"genre_scores_gemma":[0.8437089,0.002016014,0.08842806,0.000781042,0.0006000459,0.0005496611,0.0002376047,0.0006296615,0.063049],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005370887,"threshold_uncertainty_score":0.0179674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02178820701632446,"score_gpt":0.2278085092554452,"score_spread":0.2060203022391207,"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."}}