{"id":"W2430405510","doi":"10.1101/059238","title":"3D-Printed Autonomous Capillaric Circuits <sup>†</sup>","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University and Génome Québec Innovation Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research","keywords":"Cleanroom; Fluidics; Microfluidics; 3d printed; 3D printing; Electronic circuit; Printed circuit board; Capillary action; Photolithography; Materials science; Computer science; Nanotechnology; Computer hardware; Mechanical engineering; Electrical engineering; Engineering; Biomedical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002075876,0.0002784907,0.0001599279,0.0001798629,0.000142834,0.0004655129,0.000590164,0.000406976,0.002099477],"category_scores_gemma":[0.0005066053,0.0001670457,0.0002041218,0.0001294437,0.0003648926,0.0002934209,0.0001746432,0.0003170272,0.0006414375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003261916,"about_ca_system_score_gemma":0.0001657264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002855255,"about_ca_topic_score_gemma":0.0004306517,"domain_scores_codex":[0.9997392,0.00001945809,0.00002352257,0.00006092474,0.0001316839,0.00002516566],"domain_scores_gemma":[0.9995004,0.000166586,0.0001300992,0.00007482427,0.0001003894,0.00002767324],"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":[0.00004651565,0.00001872188,0.0002349993,0.00009341478,0.000007272393,0.0001376065,0.00002636081,0.002024782,0.9815777,0.001902624,0.0007779471,0.01315201],"study_design_scores_gemma":[0.000006973517,0.0000632003,0.000275397,0.000002858892,0.000005269512,0.00006776711,0.000003482922,0.006366659,0.9891468,0.0001042704,0.003948147,0.000009123023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6238803,0.001366961,0.3494366,0.0005282075,0.000838645,0.0002575024,0.001269504,0.006069757,0.01635261],"genre_scores_gemma":[0.8611293,0.0003807489,0.1315595,0.0001897823,0.00005220104,0.0001325622,0.0003870791,0.0002941171,0.005874595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002099477,"threshold_uncertainty_score":0.007023454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008082967041323047,"score_gpt":0.189076485316792,"score_spread":0.1809935182754689,"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."}}