{"id":"W2804832018","doi":"","title":"Development of an Automated Trunk Perturbation System","year":2017,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto","funders":"","keywords":"Computer science; 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":[0.0002705888,0.0004127826,0.0004713534,0.000365475,0.0005531478,0.0004610913,0.0009315152,0.000521553,0.007248342],"category_scores_gemma":[0.0004652292,0.0003081876,0.0002520538,0.0001906213,0.0002442088,0.0004124219,0.0008286558,0.0005386798,0.003289215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002403191,"about_ca_system_score_gemma":0.001075094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002210309,"about_ca_topic_score_gemma":0.00188102,"domain_scores_codex":[0.9997131,0.0000270514,0.00001392523,0.00006670284,0.000150674,0.00002851334],"domain_scores_gemma":[0.9996916,0.0000381696,0.00002378845,0.00005216431,0.0001581621,0.00003608495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004330291,0.0002966766,0.003517129,0.000434721,0.00008235378,0.0006432712,0.0004329284,0.09896304,0.4010906,0.01137734,0.007524595,0.4752044],"study_design_scores_gemma":[0.0002114204,0.001787403,0.005741857,0.00007600654,0.0001013921,0.0006990838,0.0001248229,0.7794417,0.1432416,0.002525862,0.06598269,0.00006605453],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04422991,0.00007178792,0.9321642,0.0001443519,0.0001807845,0.0005019702,0.00025594,0.009692898,0.01275829],"genre_scores_gemma":[0.5731745,0.0001460395,0.408624,0.00009064953,0.00006411148,0.000540391,0.0005564477,0.0002920045,0.01651192],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007248342,"threshold_uncertainty_score":0.02424812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008345311665733776,"score_gpt":0.2227300472164956,"score_spread":0.2143847355507618,"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."}}