{"id":"W2913027412","doi":"10.2196/10978","title":"Design, Development, and Evaluation of an Injury Surveillance App for Cricket: Protocol and Qualitative Study","year":2019,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Sports injuries and prevention","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cricket; Injury surveillance; Workload; Protocol (science); Mobile apps; Qualitative research; Health surveillance; Computer security; Medical emergency; Computer science; Human factors and ergonomics; Poison control; Medicine; World Wide Web; Environmental health","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":[0.0521327,0.0009682328,0.001633973,0.001950586,0.003969217,0.00277297,0.002385186,0.002398425,0.009753524],"category_scores_gemma":[0.04650653,0.001059342,0.001019284,0.001383085,0.00429839,0.002485584,0.00342402,0.003312215,0.002275444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006521727,"about_ca_system_score_gemma":0.021578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003959448,"about_ca_topic_score_gemma":0.006966394,"domain_scores_codex":[0.9813411,0.01198153,0.001593048,0.0013314,0.002186,0.001566886],"domain_scores_gemma":[0.9613079,0.02300936,0.001977596,0.0020712,0.009830539,0.001803448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.003074448,0.007318403,0.0112004,0.04195109,0.0001083119,0.003918054,0.657902,0.0009470214,0.01204087,0.01025006,0.02412356,0.2271657],"study_design_scores_gemma":[0.002964863,0.01090428,0.02576793,0.04619835,0.0003199266,0.002175857,0.6525801,0.001524891,0.008789781,0.008489226,0.2398999,0.0003849748],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"protocol","genre_gemma":"empirical","genre_scores_codex":[0.23845,0.001970974,0.03056397,0.003130219,0.0004222722,0.708389,0.002636509,0.000193403,0.01424363],"genre_scores_gemma":[0.09032647,0.001139482,0.02433032,0.002034674,0.00003823628,0.8769309,0.0003920293,0.00005155308,0.004756296],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0521327,"threshold_uncertainty_score":0.2757074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1467307310696825,"score_gpt":0.5263288606044725,"score_spread":0.37959812953479,"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."}}