{"id":"W3191886912","doi":"10.1007/s00216-008-2397-x","title":"Digital bioanalysis","year":2008,"lang":"en","type":"review","venue":"Analytical and Bioanalytical Chemistry","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Microfluidics; Bioanalysis; Digital microfluidics; Nanotechnology; Variety (cybernetics); Computer science; Microfluidic chip; Engineering; Materials science; Electrical engineering; Artificial intelligence","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":[0.0005829236,0.001790006,0.001257069,0.00244246,0.0005405319,0.001860242,0.002030045,0.001886237,0.0143073],"category_scores_gemma":[0.0006833653,0.0006885943,0.0004851468,0.001647029,0.001128312,0.002478889,0.002195326,0.002122543,0.01827199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000708446,"about_ca_system_score_gemma":0.0008341864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003821303,"about_ca_topic_score_gemma":0.0007150072,"domain_scores_codex":[0.9992688,0.00005313243,0.00003589235,0.0001665892,0.0004230619,0.00005259577],"domain_scores_gemma":[0.9997485,0.00006110139,0.00002277431,0.00005116842,0.00009897607,0.00001757499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003988736,0.00005634608,0.00008159952,0.001662421,0.0000245752,0.0001455933,0.00004082524,0.0002643081,0.04827025,0.01279498,0.03793553,0.8986837],"study_design_scores_gemma":[0.000006903003,0.00004659623,0.0001840868,0.0002452511,0.00002563193,0.001338024,0.00001955378,0.0005122952,0.04865522,0.003481098,0.945466,0.0000195265],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003415207,0.601745,0.2113023,0.002212731,0.007280708,0.0004468836,0.0006615089,0.002128493,0.1708071],"genre_scores_gemma":[0.02300522,0.5287358,0.08290937,0.004315345,0.002396863,0.0004847625,0.001364162,0.0001698938,0.3566186],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0143073,"threshold_uncertainty_score":0.04786265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01500437714152669,"score_gpt":0.2423934963753565,"score_spread":0.2273891192338298,"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."}}