{"id":"W2410073954","doi":"10.1097/qad.0000000000000907","title":"Use of mobile phone technology to improve the quality of point-of-care testing in a low-resource setting","year":2015,"lang":"en","type":"letter","venue":"AIDS","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alere","keywords":"Medicine; Point of care; Point-of-care testing; Psychological intervention; Quality (philosophy); Test (biology); Health care; Phone; Resource (disambiguation); Mobile phone; Risk analysis (engineering); Medical emergency; Operations management; Computer science; Nursing; Telecommunications; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002872668,0.0004849752,0.0002962823,0.0008589133,0.0004119148,0.001737068,0.0009840506,0.0008772894,0.007997439],"category_scores_gemma":[0.01394184,0.0001478173,0.0004456806,0.0006468836,0.0004610944,0.001429476,0.001453668,0.001127507,0.001837162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009257839,"about_ca_system_score_gemma":0.001339312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002307752,"about_ca_topic_score_gemma":0.002672487,"domain_scores_codex":[0.9971877,0.001184878,0.0001537689,0.0003188031,0.0009708792,0.0001840304],"domain_scores_gemma":[0.9951029,0.002038529,0.0009677875,0.000286699,0.001072034,0.000532056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003230078,0.0009774592,0.03046451,0.001105867,0.0001039539,0.0002864101,0.0006333462,0.0007272674,0.005836403,0.001651452,0.02498468,0.9329056],"study_design_scores_gemma":[0.001250405,0.01551151,0.4005741,0.009132523,0.001086548,0.005820684,0.003883184,0.01972882,0.03288216,0.01311833,0.4965627,0.0004488986],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4784118,0.08655165,0.1576405,0.08764888,0.005286075,0.004416347,0.002580451,0.006507407,0.1709568],"genre_scores_gemma":[0.8395453,0.02439416,0.1072371,0.01622603,0.002764395,0.001129812,0.0007829143,0.0001894891,0.00773092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007997439,"threshold_uncertainty_score":0.02675414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08145239243061538,"score_gpt":0.4393136866952046,"score_spread":0.3578612942645892,"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."}}