{"id":"W1978768038","doi":"10.1016/j.jbiomech.2006.08.008","title":"Quantification of the input signal for soft tissue vibration during running","year":2006,"lang":"en","type":"article","venue":"Journal of Biomechanics","topic":"Effects of Vibration on Health","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Accelerometer; SIGNAL (programming language); Vibration; Compartment (ship); Heel; Soft tissue; Acoustics; Ground reaction force; Biomedical engineering; Computer science; Materials science; Structural engineering; Physics; Engineering; Kinematics; Geology; Medicine; Surgery","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005744816,0.00007392983,0.0002062249,0.0001805512,0.00009103672,0.00001489528,0.00009164269,0.00008010414,0.00001408607],"category_scores_gemma":[0.0001193925,0.0000523206,0.0001043329,0.0002422261,0.00001675688,0.0001481171,0.00001333695,0.0001246839,0.000001454596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007768608,"about_ca_system_score_gemma":0.0001836204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009752129,"about_ca_topic_score_gemma":0.000003685235,"domain_scores_codex":[0.998859,0.0000351754,0.0005956608,0.00007870902,0.0003184092,0.0001130005],"domain_scores_gemma":[0.9985173,0.00008617876,0.0008363349,0.0001408676,0.0003729039,0.00004644331],"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":[0.0001694596,0.00009312784,0.000126562,0.0002340943,0.0000158925,0.000001496713,0.00005198181,0.0001519245,0.9919943,0.0007781496,0.0002605537,0.006122413],"study_design_scores_gemma":[0.001073386,0.0005867513,0.001690596,0.0002353351,0.00005846617,0.00009308901,0.00004526688,0.01882322,0.9756909,0.001058309,0.0005948826,0.000049804],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6601326,0.0003105913,0.3353227,0.003225944,0.0004585189,0.0005032364,0.000006337662,0.00001273727,0.00002727841],"genre_scores_gemma":[0.9911792,0.00001469602,0.008173973,0.0001082179,0.0004183512,0.000003097867,0.000006186771,0.00001516163,0.00008113585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3310466,"threshold_uncertainty_score":0.2133572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01784564456472753,"score_gpt":0.3020687175998532,"score_spread":0.2842230730351256,"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."}}