{"id":"W2616789045","doi":"10.1039/c7fd00131b","title":"Dynamic SERS nanosensor for neurotransmitter sensing near neurons","year":2017,"lang":"en","type":"article","venue":"Faraday Discussions","topic":"Gold and Silver Nanoparticles Synthesis and Applications","field":"Materials Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Institute of Neurosciences, Mental Health and Addiction; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Krembil Foundation; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Neurotransmitter; Glutamate receptor; Neuroscience; Dopamine; Electrophysiology; Acetylcholine; Chemistry; Dopaminergic; Neurotransmitter Agents; Biophysics; Nanosensor; Biology; Nanotechnology; Biochemistry; Materials science; Central nervous system; Endocrinology; Receptor","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.000123668,0.0001521015,0.0001780744,0.00002208691,0.002355804,0.0004474602,0.0003847827,0.00005076441,0.0001070007],"category_scores_gemma":[0.00008799686,0.0001008546,0.0001442774,0.0000350476,0.0001975749,0.0001951948,0.00007020374,0.00007160052,0.0001744635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001440355,"about_ca_system_score_gemma":0.00004419617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004056725,"about_ca_topic_score_gemma":0.00004952542,"domain_scores_codex":[0.9988594,0.00004011068,0.0002155491,0.0003695618,0.0001390523,0.0003763312],"domain_scores_gemma":[0.9988285,0.00008374934,0.000115433,0.0007910865,0.00003612874,0.0001450765],"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":[0.00001160743,0.00005167504,0.0001232062,0.000008271501,0.000003325344,0.00000296697,0.0001484035,0.00004820357,0.9915436,0.0008220762,0.001168487,0.006068173],"study_design_scores_gemma":[0.001456473,0.0001396796,0.05568782,0.0001459877,0.0001858975,0.00003091702,0.0004492806,0.03350513,0.7143598,0.003162688,0.1899143,0.0009620566],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9819584,0.0000148325,0.001487538,0.0149553,0.0004401344,0.0003938212,0.0001427695,0.00009448119,0.0005126951],"genre_scores_gemma":[0.9928648,0.00000653358,0.005397516,0.0003233402,0.00005362288,0.00003857796,0.000006622497,0.00002781242,0.001281205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2771838,"threshold_uncertainty_score":0.998943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02138567143261516,"score_gpt":0.2828576511849596,"score_spread":0.2614719797523445,"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."}}