{"id":"W6907970757","doi":"10.25452/figshare.plus.24255795.v1","title":"Running Injury Clinic Kinematic Dataset","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kinematics; Motion capture; Motion (physics); Metadata; Data file; Motion analysis; Trajectory; Code (set theory); MATLAB","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000330649,0.0008062865,0.000949969,0.0006705779,0.0001778431,0.000286526,0.002379523,0.0007678113,0.6993017],"category_scores_gemma":[0.009802994,0.0008319581,0.000240467,0.001073337,0.00001588543,0.0002708747,0.002022361,0.001559277,0.9855767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000162433,"about_ca_system_score_gemma":0.0003370668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001217074,"about_ca_topic_score_gemma":0.0001903364,"domain_scores_codex":[0.99591,0.0001556278,0.0009828577,0.001108252,0.0009804837,0.0008627158],"domain_scores_gemma":[0.9947796,0.0004641081,0.001018146,0.003319632,0.0001231162,0.0002953367],"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":[0.00001441703,0.00004887204,1.488e-7,0.003837403,0.0001115605,0.0003400456,0.000003478586,0.000002184335,0.000001032463,1.827199e-8,0.9956191,0.00002170533],"study_design_scores_gemma":[0.0002318918,0.0000575544,0.00004591517,0.01765975,0.0001481702,0.00001327842,0.000008025914,0.00001600887,0.0000027457,0.000006891905,0.9809489,0.0008608239],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[1.14369e-7,0.0002334586,2.148938e-9,0.00001338806,0.0003050992,0.0007668077,0.9980216,0.0006119506,0.00004757352],"genre_scores_gemma":[9.322292e-8,0.00000997264,0.00001454824,0.0003928993,0.000901126,0.000902363,0.9969245,0.0003845685,0.0004699258],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.286275,"threshold_uncertainty_score":0.9994131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1603573590535085,"score_gpt":0.4099337676588458,"score_spread":0.2495764086053373,"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."}}