{"id":"W4293150225","doi":"10.1002/smll.202203169","title":"Recent Advances of Utilizing Artificial Intelligence in Lab on a Chip for Diagnosis and Treatment","year":2022,"lang":"en","type":"review","venue":"Small","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Microfluidics; Computer science; Personalized medicine; Nanotechnology; Lab-on-a-chip; Throughput; Biochemical engineering; Artificial intelligence; Engineering; Biology; Bioinformatics; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000948974,0.0001967095,0.0005797133,0.0001577947,0.00002383168,0.000007532528,0.0001026743,0.000111127,0.00001685953],"category_scores_gemma":[0.00006837618,0.0001558489,0.00009041384,0.0001746315,0.00003336918,0.000010524,0.00004089112,0.0001197382,0.000001263774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000149178,"about_ca_system_score_gemma":0.00002153014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006981852,"about_ca_topic_score_gemma":0.0000593465,"domain_scores_codex":[0.999284,0.00001947148,0.0003050183,0.000194728,0.0000424217,0.00015441],"domain_scores_gemma":[0.999525,0.0002397194,0.00005830345,0.0001574999,0.000005647806,0.00001388148],"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":[0.000004063226,0.00003345711,0.000002955009,0.002022774,0.0000207394,0.000003101397,0.00003739448,0.000009125293,0.000002806424,0.0002838064,0.00002840545,0.9975514],"study_design_scores_gemma":[0.00002346702,0.0001768443,4.016425e-7,0.001767488,0.00005994793,0.000002124992,0.0001032698,0.00003877894,0.001134392,0.0002709359,0.9962828,0.000139531],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000250509,0.9986298,0.00008817161,0.00001518169,0.0001760134,0.0005508998,0.00006081917,0.0001010223,0.0001275893],"genre_scores_gemma":[0.00006919158,0.9987409,0.0008586265,0.000002658749,0.00002305267,0.0002540543,0.00002304524,0.00002283541,0.000005663213],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9974118,"threshold_uncertainty_score":0.6355332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1684443060001589,"score_gpt":0.3256079395352137,"score_spread":0.1571636335350548,"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."}}