{"id":"W4401282712","doi":"10.1007/s10439-024-03592-z","title":"On-field Head Acceleration Exposure Measurements Using Instrumented Mouthguards: Multi-stage Screening to Optimize Data Quality","year":2024,"lang":"en","type":"article","venue":"Annals of Biomedical Engineering","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia Hospital; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Canadian Institutes of Health Research; Canada Research Chairs; British Columbia Knowledge Development Fund; Michael Smith Health Research BC; Canada Foundation for Innovation","keywords":"Acceleration; Head (geology); Quality (philosophy); Stage (stratigraphy); Field (mathematics); Computer science; Biomedical engineering; Engineering; Physics; Mathematics; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00502456,0.001017768,0.001167409,0.001522191,0.0005208066,0.001283278,0.001058426,0.0009879129,0.002343123],"category_scores_gemma":[0.0122835,0.0005005897,0.0005296279,0.001255719,0.0002626352,0.001126828,0.001403138,0.0007192739,0.0007535891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002383916,"about_ca_system_score_gemma":0.001286367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001917431,"about_ca_topic_score_gemma":0.005246533,"domain_scores_codex":[0.9977521,0.0006534708,0.0002854062,0.0003017395,0.0008711909,0.000135918],"domain_scores_gemma":[0.9895461,0.003577852,0.0009066483,0.001399295,0.004225404,0.0003446645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004748793,0.0007557198,0.2582227,0.001184173,0.0003867653,0.0006463355,0.001159635,0.004761188,0.3165562,0.0007878398,0.006902518,0.4038881],"study_design_scores_gemma":[0.0003052148,0.002752295,0.4324323,0.0002787961,0.0008078192,0.002428713,0.001039517,0.1408343,0.4029099,0.001938065,0.01399573,0.0002773396],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5732208,0.001383289,0.4142109,0.0005241933,0.0002826141,0.0006604246,0.00212101,0.004103502,0.003493191],"genre_scores_gemma":[0.7646376,0.0005995007,0.2296169,0.0002932897,0.0001117319,0.0002883539,0.001994872,0.0005678138,0.001889952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00502456,"threshold_uncertainty_score":0.02657276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.403378788662502,"score_gpt":0.468816324976613,"score_spread":0.06543753631411092,"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."}}