{"id":"W7132995388","doi":"","title":"Non-stick surfaces for digital microfluidics","year":2008,"lang":"","type":"dissertation","venue":"TSpace","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Microfluidics; Substrate (aquarium); Adsorption; Protein adsorption; Mass spectrometry; Reagent; Digital microfluidics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002286169,0.000518299,0.0003448423,0.0003968034,0.0003938441,0.0007282388,0.0004707788,0.0006619766,0.007509664],"category_scores_gemma":[0.0004978793,0.000246036,0.0003524967,0.0003377045,0.0004385687,0.0005952314,0.0006789167,0.0009290149,0.002811304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005483481,"about_ca_system_score_gemma":0.0002374059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002512423,"about_ca_topic_score_gemma":0.0003893932,"domain_scores_codex":[0.9996549,0.00003007278,0.00001406639,0.00006014123,0.0002148026,0.00002603287],"domain_scores_gemma":[0.9998191,0.00007124969,0.00002689303,0.00002954771,0.00003684167,0.00001641878],"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":[0.00004204416,0.00005565496,0.00014401,0.0008820696,0.0000136906,0.0001819422,0.000143645,0.001328761,0.8416251,0.02574592,0.005405406,0.1244317],"study_design_scores_gemma":[0.0000251424,0.0001987775,0.0005484265,0.0001038282,0.00001861554,0.000474509,0.00007027098,0.006526696,0.7800948,0.009037131,0.2028701,0.00003178867],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1417421,0.08584727,0.6616374,0.003681773,0.00422918,0.0006729471,0.00097983,0.002869173,0.09834024],"genre_scores_gemma":[0.498431,0.04433736,0.3488224,0.001242482,0.0004994402,0.0007745435,0.001179596,0.0004176066,0.1042956],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007509664,"threshold_uncertainty_score":0.0251224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01165218989824339,"score_gpt":0.2720362466372169,"score_spread":0.2603840567389735,"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."}}