{"id":"W4220970273","doi":"10.4269/ajtmh.21-1071","title":"Point-of-Care Sample Preparation and Automated Quantitative Detection of Schistosoma haematobium Using Mobile Phone Microscopy","year":2022,"lang":"en","type":"article","venue":"American Journal of Tropical Medicine and Hygiene","topic":"Parasites and Host Interactions","field":"Immunology and Microbiology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Carleton University","funders":"","keywords":"Schistosoma haematobium; Point of care; Point-of-care testing; Computer science; Microscopy; Mobile phone; Gold standard (test); Sample (material); Automation; Biomedical engineering; Microscope; Artificial intelligence; Medicine; Biology; Pathology; Radiology; Chromatography; Schistosomiasis; Helminths; Chemistry; Telecommunications; Engineering; Immunology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006511959,0.0005118618,0.0004106408,0.0006746305,0.0003382315,0.0006500924,0.0008039169,0.001030425,0.002531776],"category_scores_gemma":[0.001652522,0.0002612932,0.0003173965,0.0003067296,0.0003830989,0.0003993145,0.0007491661,0.0005206788,0.001636259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002242705,"about_ca_system_score_gemma":0.0002836364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006405965,"about_ca_topic_score_gemma":0.001497778,"domain_scores_codex":[0.9987652,0.0003313715,0.00006362926,0.0002359283,0.0005286047,0.00007527665],"domain_scores_gemma":[0.999024,0.0004011311,0.000134358,0.0001441407,0.000243348,0.00005305502],"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":[0.0002916446,0.0001246109,0.007120953,0.000181388,0.00002514274,0.0002206737,0.00009975309,0.0004803021,0.9468243,0.0002771937,0.001325205,0.04302886],"study_design_scores_gemma":[0.00005428143,0.001713915,0.03490463,0.00007860721,0.00006190981,0.003009016,0.0001943689,0.02771225,0.9191466,0.0003705973,0.01263432,0.0001195522],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4364508,0.00141119,0.5486064,0.0006144838,0.0003751136,0.001456175,0.001475891,0.003448539,0.006161271],"genre_scores_gemma":[0.4901527,0.0009330258,0.5018174,0.0004203184,0.0001153077,0.0007844961,0.001301215,0.0001102133,0.004365309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002531776,"threshold_uncertainty_score":0.008469582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01558838272836973,"score_gpt":0.3419503881815623,"score_spread":0.3263620054531926,"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."}}