{"id":"W4399726621","doi":"10.32920/26052352","title":"Contact Pressure Based Passenger Following Seat Motion Control","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Control (management); Motion (physics); Aeronautics; Automotive engineering; Computer science; Engineering; Computer vision; Artificial intelligence","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":[0.0001302661,0.0004270591,0.0002700723,0.0002254462,0.000249032,0.0005518408,0.0005810222,0.0002487805,0.003819712],"category_scores_gemma":[0.0003181703,0.0001288919,0.0002374339,0.0001221727,0.0001538857,0.0003310084,0.0004082178,0.0002538321,0.0007136539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001746883,"about_ca_system_score_gemma":0.0002697997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002640334,"about_ca_topic_score_gemma":0.00186365,"domain_scores_codex":[0.9998517,0.00001257579,0.00000781904,0.00003736664,0.00006731039,0.00002316731],"domain_scores_gemma":[0.9998546,0.00002038726,0.00001849986,0.00001348418,0.00007906301,0.00001403233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006348378,0.0003743875,0.003070964,0.0006485495,0.00005472975,0.0002774975,0.0004013278,0.05280644,0.5270789,0.004512757,0.003520114,0.4066194],"study_design_scores_gemma":[0.0001296356,0.002027539,0.01853324,0.000055764,0.0001580119,0.0004031545,0.0001751927,0.768658,0.186868,0.001342446,0.02158787,0.00006115256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2465939,0.00102771,0.725745,0.0001386916,0.0002749002,0.0003137103,0.0002228134,0.004387791,0.02129562],"genre_scores_gemma":[0.9716661,0.0003776104,0.01891167,0.00003727119,0.0000466495,0.00009459412,0.0001436206,0.00004147439,0.008681066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003819712,"threshold_uncertainty_score":0.01277816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01289922060430298,"score_gpt":0.2967062147225102,"score_spread":0.2838069941182073,"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."}}