{"id":"W3089194368","doi":"10.3390/mi11090880","title":"Low-Cost Graphene-Based Digital Microfluidic System","year":2020,"lang":"en","type":"article","venue":"Micromachines","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microfluidics; Materials science; Microfabrication; Fabrication; Electrode; Nanotechnology; Digital microfluidics; Electrowetting; Biochip; Graphene; Lab-on-a-chip; Optoelectronics; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00004633257,0.0002902069,0.0002672052,0.0001054704,0.00009006524,0.0001173172,0.0003594983,0.0001302521,0.000009058649],"category_scores_gemma":[0.00002852005,0.0002729148,0.000130171,0.000373232,0.00006497667,0.0001085381,0.00004544231,0.0002477317,0.0001907941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005643565,"about_ca_system_score_gemma":0.00002032025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007965744,"about_ca_topic_score_gemma":6.307181e-7,"domain_scores_codex":[0.9989353,0.00001187649,0.0002639088,0.0002835549,0.00009776705,0.0004076338],"domain_scores_gemma":[0.9995489,0.0000344036,0.00003110201,0.0002560808,0.00002681736,0.000102669],"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":[0.000009781457,0.00001380965,0.001165407,0.0002909474,0.00003638778,0.00002737715,0.00008445424,0.00005889516,0.9583627,0.00005014927,0.02924851,0.01065157],"study_design_scores_gemma":[0.0004344676,0.00004042559,0.0001147612,0.00008110711,0.00001756751,0.00002516046,0.00008502329,0.0007532781,0.9643305,0.0000133828,0.03376923,0.0003351096],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9629998,0.01113745,0.01614852,0.0008642903,0.0002801604,0.0002741487,0.0001282112,0.007067695,0.001099786],"genre_scores_gemma":[0.9991147,0.000133606,0.0002419762,0.0002159702,0.0001124655,0.00002381143,0.00005856177,0.00007367695,0.00002523145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03611496,"threshold_uncertainty_score":0.9999723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006307749300318138,"score_gpt":0.1788299893762045,"score_spread":0.1725222400758863,"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."}}