{"id":"W2103102208","doi":"10.1039/b211229a","title":"MEMS technology in analytical chemistry","year":2002,"lang":"en","type":"article","venue":"The Analyst","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"University of Toronto","keywords":"Microelectromechanical systems; Microelectronics; Surface micromachining; Nanotechnology; Realization (probability); Silicon; Chip; Chemistry; Engineering; Engineering physics; Materials science; Electrical engineering; Organic chemistry","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":[0.00004694326,0.00005932599,0.00008843705,0.00004784228,0.00002906604,0.000007193819,0.0001793523,0.00005453328,0.0006567227],"category_scores_gemma":[0.000004131993,0.00004472903,0.00002950635,0.0005872032,0.00004422924,0.00001097825,0.00001389399,0.0001355612,0.0001632901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003170499,"about_ca_system_score_gemma":0.000001879082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005526724,"about_ca_topic_score_gemma":0.000002229603,"domain_scores_codex":[0.9996169,0.000003474149,0.000108588,0.00007744296,0.00004914829,0.0001445101],"domain_scores_gemma":[0.9996865,0.00001053247,0.000007424444,0.0002686174,0.000007593659,0.00001932117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001565757,0.00004628614,0.001051593,0.00001882677,0.0001095282,0.00001097166,0.0001073612,0.0003435535,0.7687934,0.005979349,0.2208666,0.002670977],"study_design_scores_gemma":[0.0004192413,0.00001714402,0.001175163,0.00001802611,0.0001350974,0.00006688647,0.0003575415,0.1110829,0.2794605,0.00443478,0.602359,0.0004737447],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9142756,0.04232578,0.0006259601,0.002368595,0.00001259942,0.00007548953,0.000002337567,0.0001992025,0.04011448],"genre_scores_gemma":[0.9885061,0.01064438,0.000004642314,0.00002760306,0.00002733853,0.00001479743,0.000002051399,0.000008176308,0.0007648791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.489333,"threshold_uncertainty_score":0.7190653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007450450163730083,"score_gpt":0.1921315806491876,"score_spread":0.1846811304854576,"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."}}