{"id":"W2073421801","doi":"10.1115/dscc2013-4005","title":"Cycle-by-Cycle Based In-Cylinder Temperature Estimation for Diesel Engines","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Cylinder; Crank; Automotive engineering; Combustion; Control theory (sociology); Kalman filter; Extended Kalman filter; Temperature measurement; Internal combustion engine; Ignition system; Power (physics); Engineering; Computer science; Mechanical engineering; Thermodynamics; Physics; Aerospace engineering; Chemistry","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":[0.0002657923,0.0003789797,0.0003919685,0.0003918736,0.0002229542,0.000340825,0.0004634183,0.00025612,0.0003550744],"category_scores_gemma":[0.0008737876,0.0002246236,0.0002142862,0.0003083522,0.0001391931,0.0003915282,0.0002358842,0.0003027488,0.0001332463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003501243,"about_ca_system_score_gemma":0.0006099691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01048004,"about_ca_topic_score_gemma":0.01234571,"domain_scores_codex":[0.9998717,0.00002013229,0.000008548191,0.0000370089,0.00005096379,0.0000115175],"domain_scores_gemma":[0.9998066,0.00006108051,0.00004205087,0.00001868786,0.00006416102,0.00000753329],"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":[0.0003143058,0.0001075244,0.01017065,0.0002205814,0.00007559892,0.00008586224,0.0001191431,0.6335942,0.05408209,0.001344898,0.0009270876,0.2989581],"study_design_scores_gemma":[0.000003501775,0.00002816723,0.002265262,0.000002952172,0.00000698515,0.00001346702,0.000005144219,0.9894645,0.007657551,0.0001416891,0.0003992829,0.00001153355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2163942,0.0007495868,0.7792891,0.00008482973,0.00006266566,0.00006422745,0.0001862644,0.0008523769,0.002316781],"genre_scores_gemma":[0.9710256,0.0001568254,0.02795993,0.00001178394,0.000008404852,0.00002489897,0.0001142674,0.00002436858,0.0006738444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01048004,"threshold_uncertainty_score":0.02083808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006281058761676836,"score_gpt":0.2310774734216735,"score_spread":0.2247964146599966,"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."}}