{"id":"W4408903684","doi":"10.1021/acssensors.5c00355","title":"MIP-Chip: Integrated Microfluidic Plasma Separation and Redox-Enhanced Molecularly Imprinted Polymer Succinate Sensor for Whole Blood Metabolite Analysis","year":2025,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Molecularly imprinted polymer; Microfluidics; Metabolite; Chromatography; Chemistry; Polymer; Molecular imprinting; Microfluidic chip; Materials science; Nanotechnology; Selectivity; Organic chemistry; Biochemistry; Catalysis","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":[0.0003904107,0.000786651,0.0004383576,0.0004069405,0.0001298534,0.0002865848,0.0008847559,0.0007586032,0.0009235378],"category_scores_gemma":[0.000363829,0.0003783079,0.000508211,0.0002481549,0.0001915374,0.0004282078,0.0004889593,0.0005458809,0.0006310467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003386337,"about_ca_system_score_gemma":0.0005003075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004594739,"about_ca_topic_score_gemma":0.0005368717,"domain_scores_codex":[0.9995897,0.00004314106,0.00002411594,0.0001434897,0.0001487835,0.00005072707],"domain_scores_gemma":[0.9998412,0.00004010932,0.00004047138,0.00001227456,0.00004686518,0.0000190284],"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":[0.00008159722,0.0000477771,0.0002547032,0.0001780645,0.0000281954,0.00006591932,0.00001340649,0.00052276,0.9854743,0.0002791371,0.0005662476,0.01248787],"study_design_scores_gemma":[0.00001275823,0.0001538701,0.0009733721,0.00000738484,0.00002439372,0.0002067551,0.000005216379,0.008517772,0.9859629,0.00005586565,0.004056615,0.00002297427],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.341352,0.01309566,0.6274331,0.0009754468,0.0008080271,0.0006325268,0.002799844,0.007535262,0.005368197],"genre_scores_gemma":[0.4822449,0.004898168,0.5025403,0.001339635,0.0001895681,0.000772053,0.002196315,0.0001450403,0.00567393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009235378,"threshold_uncertainty_score":0.003089547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003746894520635792,"score_gpt":0.2227824551824528,"score_spread":0.219035560661817,"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."}}