{"id":"W1911704687","doi":"10.2196/rehab.4120","title":"Mobile Jump Assessment (mJump): A Descriptive and Inferential Study","year":2015,"lang":"en","type":"article","venue":"JMIR Rehabilitation and Assistive Technologies","topic":"Sports Performance and Training","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Jump; Statistics; Descriptive statistics; Computer science; Psychology; Mathematics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005534406,0.000282221,0.0008531697,0.001850289,0.0005710571,0.0006084957,0.0006210844,0.000495153,0.00193034],"category_scores_gemma":[0.01107093,0.0003128162,0.0007725776,0.001263159,0.0006422795,0.0009331275,0.001076081,0.0005478149,0.0002757803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004151644,"about_ca_system_score_gemma":0.0006674814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00101693,"about_ca_topic_score_gemma":0.001180256,"domain_scores_codex":[0.9959458,0.001705947,0.0004763454,0.0004964921,0.001012367,0.0003631052],"domain_scores_gemma":[0.9925448,0.005105008,0.001156393,0.0003642428,0.0005117821,0.0003178146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009595443,0.001415022,0.9857896,0.000179227,0.0001382117,0.000256157,0.001649839,0.00006146128,0.0003794506,0.000117436,0.0001490628,0.008905177],"study_design_scores_gemma":[0.0001302348,0.006312773,0.9847717,0.00008878302,0.0001658801,0.0006760865,0.005962549,0.001088802,0.000191672,0.0001621174,0.0004279615,0.000021484],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987663,0.0001193094,0.0004674901,0.00001310563,0.000004754094,0.0002096341,0.0001326035,0.000003424914,0.0002834103],"genre_scores_gemma":[0.9985908,0.00005531422,0.0006483907,0.00003066703,0.000008201763,0.0004034594,0.0001439281,0.000002536198,0.0001166552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005534406,"threshold_uncertainty_score":0.0292691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03580815525249946,"score_gpt":0.353844110580498,"score_spread":0.3180359553279986,"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."}}