{"id":"W3215195458","doi":"10.20944/preprints202111.0507.v1","title":"Modeling The Sport Differential Mechanism","year":2021,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Transportation Systems and Logistics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Torque; Computer science; Kinematics; Mechanism (biology); Curvilinear coordinates; Axle; Modeling and simulation; Scope (computer science); Differential (mechanical device); Control engineering; Control theory (sociology); Simulation; Engineering; Control (management); Mechanical engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002572519,0.0003507532,0.0004363102,0.00006285453,0.00008717284,0.0000555743,0.0005226371,0.0003527276,0.0006490949],"category_scores_gemma":[0.00001640719,0.0003004544,0.0002566367,0.00007774965,0.00002546011,0.00004640392,0.0002865864,0.0009748857,0.0001853063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007015967,"about_ca_system_score_gemma":0.00006612503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002794338,"about_ca_topic_score_gemma":0.00009956369,"domain_scores_codex":[0.9982004,0.00002730874,0.0006041728,0.000516129,0.0003556967,0.0002963293],"domain_scores_gemma":[0.9985904,0.00001632167,0.00007466561,0.001111566,0.0001144139,0.00009266547],"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":[0.000005935373,0.00003320384,0.01989533,0.0004597227,0.0002834241,0.00004368192,0.001853505,0.9685226,0.003676106,0.005099763,0.000008461063,0.0001182628],"study_design_scores_gemma":[0.0004817695,0.000005730316,0.09671694,0.0005573974,0.0003595314,0.00002212257,0.001137759,0.8785715,0.01562039,0.003746797,0.001447491,0.00133256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.849741,0.0001577262,0.1445505,0.00003485024,0.002513292,0.0003387195,0.00002611479,0.0004675992,0.002170162],"genre_scores_gemma":[0.9985228,0.0002164217,0.0002139408,0.00002299897,0.0003752417,0.0001356854,0.0001533478,0.00007961633,0.0002799458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1487818,"threshold_uncertainty_score":0.9999447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1067585928824624,"score_gpt":0.2926078176618399,"score_spread":0.1858492247793774,"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."}}