{"id":"W3128332301","doi":"10.22541/au.157533115.54624508","title":"Induced-charge electrokinetic (ICEK) development and applications in microfluidics","year":2019,"lang":"en","type":"dataset","venue":"Authorea","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microfluidics; Electrokinetic phenomena; Nanotechnology; Digital microfluidics; Electric field; Materials science; Engineering; Electrical engineering; Physics; Voltage; Electrowetting","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001231697,0.0003288454,0.0003407708,0.0003197747,0.00004712908,0.00003719611,0.0002915496,0.0006201785,0.00001974488],"category_scores_gemma":[0.00001783351,0.0003153891,0.00002869296,0.0002650968,0.00004200867,0.00002859503,0.0001301974,0.0006039741,0.0002163687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001177689,"about_ca_system_score_gemma":0.0000615633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003561489,"about_ca_topic_score_gemma":0.00002342967,"domain_scores_codex":[0.998848,0.00001215692,0.0003246577,0.0003328637,0.0001164264,0.0003659382],"domain_scores_gemma":[0.9993539,0.00004202546,0.0000494077,0.0004898215,0.00001952333,0.00004528052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001293184,0.00001956385,0.00004121707,0.0001945905,0.0000240997,0.000005618479,0.00002493414,3.268353e-7,0.02098908,0.00005029128,0.9742581,0.004390845],"study_design_scores_gemma":[0.0001036691,0.00001541171,0.0002120264,0.00007611848,0.00002307057,0.00001305494,0.00002567251,0.00001121212,0.04949331,0.00003823904,0.9496347,0.0003534804],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03853342,0.01984223,0.0004749368,0.0001137871,0.0004685667,0.001354105,0.9381505,0.0007817287,0.0002806968],"genre_scores_gemma":[0.006716347,0.006798554,0.0004232686,0.0000413644,0.00007596012,0.00008970476,0.9856961,0.00005465958,0.0001039752],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04754563,"threshold_uncertainty_score":0.9999298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0193095291367091,"score_gpt":0.2296223167855312,"score_spread":0.2103127876488221,"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."}}