{"id":"W4253801646","doi":"10.1039/c4lc01366b","title":"Integrating nanopore sensors within microfluidic channel arrays using controlled breakdown","year":2015,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Nanopore and Nanochannel Transport Studies","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Canada Foundation for Innovation","keywords":"Nanopore; Microfluidics; Channel (broadcasting); Nanotechnology; Nanopore sequencing; Materials science; Optoelectronics; Engineering; Chemistry; Electrical 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":[0.0002624667,0.0003935133,0.0002464214,0.0002901595,0.0001794308,0.0005078921,0.0005321393,0.0005343841,0.0004974081],"category_scores_gemma":[0.0004926113,0.0003421189,0.0001832526,0.0001981001,0.0002882787,0.0006962552,0.0005039095,0.0004177116,0.0002406204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004675682,"about_ca_system_score_gemma":0.0003574946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004369398,"about_ca_topic_score_gemma":0.0006788669,"domain_scores_codex":[0.9996871,0.00002561067,0.00001990736,0.00009289163,0.0001232435,0.00005126403],"domain_scores_gemma":[0.9995822,0.0001542307,0.0001151188,0.00004380782,0.00006166032,0.00004297185],"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":[0.00001568732,0.00001547756,0.00008837476,0.00002803472,0.000002415687,0.00001561277,0.000008339841,0.0001739795,0.9972566,0.0001672037,0.00004378541,0.002184594],"study_design_scores_gemma":[0.000006034994,0.00006152466,0.0003898533,0.000002155742,0.000003118294,0.00006636636,0.000005492232,0.003151313,0.9951265,0.00009533353,0.00108472,0.000007601206],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8500038,0.002432376,0.1414158,0.0002860313,0.00029278,0.0002178989,0.0006459938,0.001572971,0.003132287],"genre_scores_gemma":[0.8825168,0.001074645,0.1122186,0.0001926439,0.00005785743,0.0001859652,0.0004473842,0.00005469244,0.003251414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005343841,"threshold_uncertainty_score":0.003392458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0281424020512738,"score_gpt":0.2326866112441157,"score_spread":0.2045442091928419,"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."}}