{"id":"W2941892867","doi":"10.1109/tbme.2019.2913308","title":"Motion-Based Prediction of Hands and Feet Contact Efforts During Asymmetric Handling Tasks","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut de recherche Robert-Sauvé en santé et en sécurité du travail","funders":"","keywords":"Ground reaction force; Work (physics); Simulation; Set (abstract data type); Task (project management); Contact force; Instrumentation (computer programming); Mean squared error; Computer science; Contact area; Motion (physics); Biomechanics; Engineering; Kinematics; Mathematics; Mechanical engineering; Artificial intelligence; Statistics; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009419787,0.0001851813,0.0002433244,0.0007506879,0.00006646178,0.00001619276,0.00005878723,0.0001215942,0.00003587285],"category_scores_gemma":[0.000008245673,0.0001882734,0.00008854054,0.0007235135,0.00002691893,0.0001118936,8.856863e-7,0.0002477969,0.000002052101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006354647,"about_ca_system_score_gemma":0.000009703238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001007733,"about_ca_topic_score_gemma":0.000001024694,"domain_scores_codex":[0.9990151,0.000007603277,0.0002860226,0.0001885269,0.0002524293,0.0002503138],"domain_scores_gemma":[0.9995666,0.0001125266,0.00002900053,0.0001446068,0.00003011554,0.0001171959],"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":[0.00007662683,0.0002083795,0.001096274,0.001020193,0.000492645,0.000004926658,0.000258567,0.7146173,0.2235334,0.00003832163,0.00005336216,0.05859996],"study_design_scores_gemma":[0.003582392,0.0003808477,0.04284515,0.0003423742,0.00005543004,0.00001064898,0.00003869069,0.7251884,0.2266838,0.00000343158,0.0005093617,0.0003595197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6275192,0.00008439107,0.3713909,0.0000191886,0.0004731926,0.0001402445,0.0000233511,0.0002748347,0.00007470023],"genre_scores_gemma":[0.9994678,0.0001150738,0.0002882412,0.000009192868,0.00003820664,0.00002957136,0.000008016926,0.00003186311,0.00001201031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3719486,"threshold_uncertainty_score":0.7677566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004739446150007987,"score_gpt":0.1775500472425086,"score_spread":0.1728106010925006,"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."}}