{"id":"W2146602797","doi":"10.1002/adfm.201402218","title":"Dynamic Fluoroalkyl Polyethylene Glycol Co‐Polymers: A New Strategy for Reducing Protein Adhesion in Lab‐on‐a‐Chip Devices","year":2014,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Interface Biologics (Canada); University of Toronto","funders":"University of Toronto; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Materials science; Ethylene glycol; Biofouling; Microfluidics; Protein adsorption; Wetting; Polymer; Adsorption; Biomolecule; Contact angle; Polyethylene glycol; Nanotechnology; Coating; Bioconjugation; Surface modification; Methacrylate; Surface energy; Adhesion; Chemical engineering; Copolymer; Organic chemistry; Membrane; Chemistry; Composite material","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":[0.0001466294,0.0005986856,0.0001373874,0.0002196893,0.0001237705,0.000261291,0.0003440273,0.0004116354,0.0005563261],"category_scores_gemma":[0.0001519183,0.0002018011,0.0002075169,0.000137904,0.0001707586,0.000514005,0.0001857804,0.000473378,0.0002718421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002655595,"about_ca_system_score_gemma":0.0001511341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000339821,"about_ca_topic_score_gemma":0.0006384563,"domain_scores_codex":[0.9998938,0.00001015268,0.000006988371,0.00003159128,0.00003913298,0.00001834831],"domain_scores_gemma":[0.9999341,0.00001217322,0.00002892211,0.000007588426,0.000006820956,0.00001045051],"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":[0.0000102815,0.00002214125,0.00002234658,0.00003062378,0.000002787134,0.00002014775,0.00000813612,0.00008936057,0.9973012,0.0001337563,0.0000385244,0.002320908],"study_design_scores_gemma":[0.000005084422,0.00008833564,0.0002623344,0.000002643195,0.000005883713,0.00007573278,0.000002920139,0.0006484871,0.9964653,0.00002532822,0.002412923,0.000004924303],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8933678,0.006234244,0.09418555,0.0004155942,0.0001680815,0.0001745896,0.0002687594,0.0004295098,0.00475572],"genre_scores_gemma":[0.9271507,0.003971793,0.06276037,0.0003034876,0.0000447599,0.0001405719,0.0001866759,0.00005732986,0.005384349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005986856,"threshold_uncertainty_score":0.00192672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01173613437083892,"score_gpt":0.2410002673034205,"score_spread":0.2292641329325815,"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."}}