{"id":"W3089304786","doi":"10.1123/jab.2020-0047","title":"Estimating Muscle Forces for Breast Cancer Survivors During Functional Tasks","year":2020,"lang":"en","type":"article","venue":"Journal of Applied Biomechanics","topic":"Shoulder Injury and Treatment","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Saskatchewan","funders":"","keywords":"Breast cancer; Electromyography; Physical medicine and rehabilitation; Kinematics; Medicine; Physical therapy; Rehabilitation; Repeated measures design; Analysis of variance; Cancer; Mathematics; Internal medicine; Statistics","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":[0.0001346119,0.0001322794,0.0002849874,0.00008338417,0.0001048426,0.00001892345,0.00006558565,0.00007112089,0.0001440838],"category_scores_gemma":[0.00001495476,0.0001007534,0.0001551042,0.000184931,0.0000134424,0.00006325446,0.00002473948,0.0001492252,0.000004345045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000897932,"about_ca_system_score_gemma":0.0001041471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006273047,"about_ca_topic_score_gemma":0.000003181268,"domain_scores_codex":[0.9990347,0.000004691087,0.0003566336,0.0001445085,0.0002796752,0.0001798085],"domain_scores_gemma":[0.9992648,0.00003982403,0.0002841253,0.00007266018,0.000143002,0.0001955639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.006412392,0.0004201174,0.0003299396,0.0007575753,0.001074172,0.00008456793,0.0009327342,0.001254413,0.8721325,0.001402749,0.001174815,0.114024],"study_design_scores_gemma":[0.02543697,0.003357094,0.012499,0.0005234568,0.003780911,0.001651599,0.003318448,0.07364292,0.8599034,0.006291166,0.008581419,0.001013623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747571,0.0001366822,0.01992632,0.003845602,0.0006464151,0.0003761503,0.0001144638,0.00003562395,0.0001616328],"genre_scores_gemma":[0.988619,0.00002094051,0.009538563,0.0005719946,0.001174585,0.00002022275,0.000008465439,0.00002421567,0.00002199661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1130103,"threshold_uncertainty_score":0.4108604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03082108314782822,"score_gpt":0.2876129367315831,"score_spread":0.2567918535837549,"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."}}