{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002905603,0.0006303038,0.0004485561,0.0009485965,0.0003662963,0.001017365,0.001390059,0.000938391,0.005772856],"category_scores_gemma":[0.0004624389,0.0002201231,0.0008345521,0.000552405,0.0006868984,0.0009321989,0.0009757074,0.0004652282,0.0008488853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004701992,"about_ca_system_score_gemma":0.0008449547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002799834,"about_ca_topic_score_gemma":0.00132969,"domain_scores_codex":[0.999808,0.0000351643,0.00001529534,0.00004733828,0.00006960751,0.00002467835],"domain_scores_gemma":[0.9998773,0.00002516381,0.00003284709,0.00002107417,0.00003324887,0.0000102782],"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":[0.00004788642,0.00006500254,0.002563705,0.0003009881,0.00004213181,0.0006815665,0.0002923215,0.6510797,0.01248436,0.3008709,0.001524189,0.03004732],"study_design_scores_gemma":[0.00002024219,0.0001102389,0.0008784976,0.00003610813,0.00002134363,0.0004196927,0.00007880673,0.9377356,0.001504789,0.03805144,0.02112048,0.00002271892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04155345,0.001202943,0.9164294,0.0002619468,0.0001824127,0.0001835924,0.000412071,0.0002987138,0.03947549],"genre_scores_gemma":[0.8337592,0.003021017,0.117348,0.0001279612,0.0001666778,0.0006105371,0.0005714044,0.0001174871,0.04427772],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005772856,"threshold_uncertainty_score":0.01931214,"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."}}