{"id":"W4406986162","doi":"10.1007/s10439-025-03690-6","title":"Correction: Optimising Instrumented Mouthguard Data Analysis: Video Synchronisation Using a Cross-correlation Approach","year":2025,"lang":"en","type":"erratum","venue":"Annals of Biomedical Engineering","topic":"Dental Trauma and Treatments","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Mouthguard; Correlation; Computer science; Data mining; Medicine; Mathematics; Dentistry","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":[0.003537217,0.00227913,0.001621906,0.003960285,0.002634619,0.003194807,0.002588344,0.007834803,0.07379931],"category_scores_gemma":[0.09947743,0.001306372,0.001269542,0.002252151,0.002275492,0.001833077,0.002181414,0.008431857,0.04690207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002215583,"about_ca_system_score_gemma":0.004661143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.016952,"about_ca_topic_score_gemma":0.020322,"domain_scores_codex":[0.9939726,0.0007715089,0.001254538,0.0006074206,0.003025173,0.0003686519],"domain_scores_gemma":[0.9443249,0.01139791,0.002967326,0.0038759,0.03597108,0.001462908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008195708,0.00001025686,0.0001179696,0.0002132424,0.00001413513,0.0005563021,0.00006961446,0.00006803863,0.0002372638,0.0006012508,0.9821916,0.01583828],"study_design_scores_gemma":[0.00007283146,0.00004051177,0.001170591,0.0004945265,0.00004810428,0.001486397,0.0001868704,0.0009119356,0.001627016,0.001742015,0.992151,0.00006824125],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0003838141,0.0006094578,0.003827877,0.02917462,0.960093,0.00006698566,0.001386666,0.00170406,0.002753565],"genre_scores_gemma":[0.04140959,0.00664425,0.05403952,0.08317002,0.3960634,0.0008110309,0.004884801,0.009105618,0.4038718],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.07379931,"threshold_uncertainty_score":0.2468833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1521090408288417,"score_gpt":0.4604342900872379,"score_spread":0.3083252492583962,"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."}}