{"id":"W1983564278","doi":"10.1021/ac501473c","title":"Plasmonic Nanopipette Biosensor","year":2014,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Gold and Silver Nanoparticles Synthesis and Applications","field":"Materials Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de l'Enseignement Supérieur, de la Recherche, de la Science et de la Technologie; Max-Planck-Gesellschaft; Alexander von Humboldt-Stiftung","keywords":"Plasmon; Biomolecule; Chemistry; Nanotechnology; Biosensor; Plasmonic nanoparticles; Raman spectroscopy; Nanoparticle; Colloidal gold; Immunoassay; Optoelectronics; Materials science; Optics; Antibody","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":[0.0003325538,0.0006416998,0.0005747558,0.0004242049,0.0004251362,0.0005202531,0.001819244,0.001739584,0.002284809],"category_scores_gemma":[0.0004063239,0.0005120297,0.0003836846,0.0003669453,0.000280824,0.0005533939,0.0006636996,0.00104274,0.001919737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007984997,"about_ca_system_score_gemma":0.000286398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006976427,"about_ca_topic_score_gemma":0.001105278,"domain_scores_codex":[0.999248,0.00005754396,0.00004679058,0.000266929,0.0003094514,0.0000712734],"domain_scores_gemma":[0.9997672,0.0000547021,0.00003328893,0.00002446271,0.00009292133,0.000027365],"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":[0.00002741616,0.00001688413,0.00004666996,0.00005820858,0.000005480937,0.00005484475,0.00001195917,0.0001055186,0.9965333,0.0001469022,0.0002376014,0.002755167],"study_design_scores_gemma":[0.000007943435,0.000128678,0.0005529869,0.000005556285,0.00001719479,0.0003641024,0.00001120019,0.004625272,0.9890449,0.00006752627,0.005159196,0.00001543278],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3747268,0.005857468,0.585784,0.001639929,0.00157868,0.001020599,0.003332572,0.009515569,0.01654447],"genre_scores_gemma":[0.5694071,0.002528684,0.3965764,0.001524536,0.0002512627,0.0008165427,0.002405897,0.0001508465,0.02633883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002284809,"threshold_uncertainty_score":0.007643402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008473533286805736,"score_gpt":0.2171991989693439,"score_spread":0.2087256656825382,"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."}}