{"id":"W3176616755","doi":"10.3390/s21134473","title":"Validation of a 3D Camera System for Cycling Analysis","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Intraclass correlation; Gold standard (test); Kinematics; Motion capture; Motion analysis; Amateur; Cycling; Computer science; Video camera; Artificial intelligence; Computer vision; Mathematics; Statistics; Motion (physics); Reproducibility; Geography; Physics","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":[0.00673112,0.0008613852,0.0004545306,0.001435988,0.0004277758,0.0007773978,0.001063018,0.0008946335,0.002258664],"category_scores_gemma":[0.01252988,0.0002909792,0.0004900306,0.0006682067,0.0008139449,0.0006380864,0.001183419,0.0003461356,0.0009660246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004606695,"about_ca_system_score_gemma":0.0008503737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001217883,"about_ca_topic_score_gemma":0.001951842,"domain_scores_codex":[0.9921432,0.002610959,0.0006697198,0.001541359,0.002816108,0.0002186366],"domain_scores_gemma":[0.9893898,0.002718679,0.001066249,0.001478689,0.005061882,0.0002846844],"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":[0.001785106,0.0004757001,0.331087,0.001214895,0.0003437854,0.000275996,0.001361997,0.002858487,0.3562366,0.001100467,0.001944396,0.3013157],"study_design_scores_gemma":[0.0001399127,0.004865976,0.7414564,0.0005154446,0.0005667966,0.00374475,0.00100835,0.02728757,0.2065409,0.0006818803,0.01304542,0.0001465261],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6855525,0.001496042,0.3040969,0.0001894249,0.0002245872,0.001202523,0.0009008215,0.0009321311,0.005405171],"genre_scores_gemma":[0.8409576,0.0003932723,0.1555631,0.000171573,0.00005071668,0.000626309,0.0009472215,0.0001108683,0.001179292],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00673112,"threshold_uncertainty_score":0.03559798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.033298793254108,"score_gpt":0.3665456098972831,"score_spread":0.3332468166431751,"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."}}