{"id":"W3024538946","doi":"10.1149/ma2020-016660mtgabs","title":"Optimisation of Dyes@SWCNT Raman Nanoprobes","year":2020,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Regroupement Québécois sur les Matériaux de Pointe; Université de Montréal","funders":"","keywords":"Raman scattering; Carbon nanotube; Materials science; Raman spectroscopy; Nanotechnology; Zeta potential; Dynamic light scattering; Dispersion (optics); Drug delivery; Chemical engineering; Nanoparticle; Optics","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":[0.001702505,0.001341053,0.0005292812,0.0005549764,0.0002971029,0.0005616966,0.0006745929,0.0009310059,0.001541399],"category_scores_gemma":[0.001614543,0.0006287364,0.0003507223,0.0002792653,0.0003776772,0.0004889838,0.000419329,0.0005114957,0.001308748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005882748,"about_ca_system_score_gemma":0.0002824587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006267939,"about_ca_topic_score_gemma":0.001980582,"domain_scores_codex":[0.9988899,0.0002598651,0.0001177753,0.000296366,0.0003120838,0.0001240008],"domain_scores_gemma":[0.9988499,0.0004610068,0.0001714829,0.00009415074,0.0003421323,0.00008145371],"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":[0.00001944238,0.00001436477,0.00003346577,0.00004676112,0.00000400987,0.00001773016,0.00001283408,0.0002425957,0.9988187,0.00004651924,0.0000279392,0.0007156123],"study_design_scores_gemma":[0.000003662414,0.00004510235,0.0001612406,0.000003409431,0.000005271015,0.00002484864,0.000008724515,0.001062949,0.9980825,0.000009312093,0.0005878933,0.000004990621],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9063921,0.002373022,0.08626375,0.0003331151,0.0001335277,0.0007233719,0.0006433491,0.0009589137,0.002178866],"genre_scores_gemma":[0.7415882,0.002858046,0.2467364,0.0002602423,0.0000449895,0.0009563729,0.00108574,0.0005364435,0.005933559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001702505,"threshold_uncertainty_score":0.009003818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01779899286785122,"score_gpt":0.2151029465081958,"score_spread":0.1973039536403446,"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."}}