{"id":"W4402229006","doi":"10.1002/advs.202405712","title":"Toward Analysis at the Point of Need: A Digital Microfluidic Approach to Processing Multi‐Source Sexual Assault Samples","year":2024,"lang":"en","type":"article","venue":"Advanced Science","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Sexual assault; STR analysis; Microfluidics; Computer science; Microsatellite; Biology; Poison control; Medicine; Nanotechnology; Materials science; Genetics; Medical emergency; Human factors and ergonomics","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":[0.000354061,0.0001660323,0.0001979514,0.0003748854,0.0001737373,0.0001806294,0.0005742739,0.00005056617,0.00000178254],"category_scores_gemma":[0.0002140628,0.0001150023,0.00006765691,0.003545434,0.0004018351,0.0003836904,0.0001870328,0.0001954983,0.000009993673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001553424,"about_ca_system_score_gemma":0.00006448761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002022384,"about_ca_topic_score_gemma":0.000003210467,"domain_scores_codex":[0.9986248,0.000006572689,0.0002209914,0.0004117989,0.0003066215,0.0004292127],"domain_scores_gemma":[0.9994386,0.00007151969,0.00002691381,0.0003312438,0.00007201761,0.0000596682],"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":[0.000002520738,0.00001173567,0.0001832557,0.00006633928,0.00003747772,0.000001058938,0.001497373,0.006968453,0.8580452,0.00004220401,0.0003020868,0.1328423],"study_design_scores_gemma":[0.00009574781,0.00005226147,0.0003579597,0.00005902667,0.00007856771,0.00002767327,0.003857705,0.01815868,0.967636,0.00005451742,0.009338843,0.0002830538],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6201168,0.0131698,0.3652638,0.0001521919,0.00005834269,0.000135028,0.00001763497,0.0007485626,0.0003378245],"genre_scores_gemma":[0.9915031,0.00008564102,0.008007531,0.00002854264,0.00001164398,0.00002361888,0.000005059854,0.00001932983,0.000315506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3713863,"threshold_uncertainty_score":0.4689659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715871684708516,"score_gpt":0.2475091719698843,"score_spread":0.2303504551227992,"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."}}