{"id":"W2263375012","doi":"10.1155/2016/1241862","title":"Near-Infrared Spectroscopic Screening for Bladder Disease in Africa: Training Rural Clinic Staff to Collect Data of Diagnostic Quality","year":2016,"lang":"en","type":"article","venue":"Journal of Spectroscopy","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Mbarara University of Science and Technology; Grand Challenges Canada","keywords":"Medicine; Data collection; Protocol (science); Quality (philosophy); Upload; Orientation (vector space); Medical physics; Family medicine; Physical therapy; Medical education; Alternative medicine; Pathology; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001441725,0.0002153571,0.0005247782,0.0001486997,0.00006150706,0.00003510542,0.001028413,0.0001494223,0.0002062966],"category_scores_gemma":[0.00808489,0.0001526506,0.0001897308,0.0003302479,0.0002810839,0.00002403431,0.0003428193,0.0002359494,0.000003318865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009513995,"about_ca_system_score_gemma":0.0005692379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009700694,"about_ca_topic_score_gemma":0.000009242057,"domain_scores_codex":[0.9973221,0.0001141445,0.0009886553,0.0003925121,0.0005463582,0.0006362373],"domain_scores_gemma":[0.9975355,0.0007556368,0.0003794673,0.0006791941,0.0002018538,0.0004483812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002389982,0.0002916708,0.006909682,0.00005016588,0.00009407639,0.00001495509,0.00007548893,0.000001443634,0.9680282,0.00005726233,0.02082423,0.001262883],"study_design_scores_gemma":[0.003951337,0.004885938,0.01116237,0.0007188621,0.00007652991,0.000009025496,0.0002623833,0.00004781255,0.9486231,0.004510573,0.0253175,0.0004346311],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.920612,0.000964925,0.07508889,0.001738042,0.0001697811,0.000541609,0.0002869616,0.00001247205,0.0005852914],"genre_scores_gemma":[0.9408954,0.0008251659,0.05681227,0.0001148532,0.0005188693,0.00003340402,0.00004082036,0.00003800076,0.0007212389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02028335,"threshold_uncertainty_score":0.9678952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08836945405797135,"score_gpt":0.4145142243767516,"score_spread":0.3261447703187803,"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."}}