{"id":"W4388235503","doi":"10.2196/50897","title":"Experiences, Lessons, and Challenges With Adapting REDCap for COVID-19 Laboratory Data Management in a Resource-Limited Country: Descriptive Study","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Descriptive research; Descriptive statistics; Data science; Business; Computer science; Medicine; Virology; Sociology; Statistics","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":[0.02131836,0.000657811,0.0008838868,0.001426268,0.008166875,0.006130435,0.002503893,0.001933336,0.001405833],"category_scores_gemma":[0.0445731,0.001347432,0.0006398156,0.002027614,0.006305333,0.006948818,0.007643692,0.004091564,0.0002917743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005913813,"about_ca_system_score_gemma":0.00924295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01517952,"about_ca_topic_score_gemma":0.02432832,"domain_scores_codex":[0.9827171,0.0119729,0.0006344664,0.0007549234,0.001255285,0.002665339],"domain_scores_gemma":[0.9701496,0.01920513,0.003136862,0.001031322,0.00312525,0.00335181],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00002861057,0.0001096797,0.01392641,0.0002396358,0.00001014292,0.001689427,0.9749648,0.00006214006,0.0004092766,0.0005322515,0.0006961475,0.007331396],"study_design_scores_gemma":[0.000002497194,0.00006701688,0.003218662,0.0001281537,0.000004296296,0.000323932,0.9916222,0.00008939432,0.0001149743,0.00009639154,0.004315308,0.00001726056],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944966,0.0003155531,0.0009118087,0.001938127,0.00003180357,0.0001762611,0.00007196579,0.00001436676,0.002043528],"genre_scores_gemma":[0.9949259,0.0007849469,0.001696652,0.001045736,0.00001621906,0.0003019101,0.00006333512,0.00002678769,0.001138486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02131836,"threshold_uncertainty_score":0.1127436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3142281035776542,"score_gpt":0.4491743109258066,"score_spread":0.1349462073481524,"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."}}