{"id":"W2800428248","doi":"10.1149/ma2018-01/16/1148","title":"(Invited) In Situ Accurate Analysis of Colloidal Nanoparticles via Four Wave Mixing","year":2018,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Nanoparticle; Materials science; Molecular physics; Optics; Four-wave mixing; Particle (ecology); Optical tweezers; Laser; Plasmonic nanoparticles; Particle size; Nanotechnology; Chemical physics; Physics; Chemistry; Nonlinear 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":[0.0003427416,0.0005537494,0.000338085,0.0006273973,0.000270173,0.0004640115,0.0007009132,0.0008687584,0.003389329],"category_scores_gemma":[0.000416738,0.0002710655,0.0002848895,0.000344244,0.000454359,0.0008503365,0.001028889,0.0009206044,0.001594497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003487379,"about_ca_system_score_gemma":0.0001839778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002345892,"about_ca_topic_score_gemma":0.0002507735,"domain_scores_codex":[0.9995847,0.00005179627,0.00001960141,0.0001343239,0.0001774947,0.00003207298],"domain_scores_gemma":[0.9997702,0.0000471483,0.00006044985,0.00005447004,0.00005166024,0.00001609227],"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":[0.00003809582,0.00001001214,0.0001977218,0.00006810143,0.000004748516,0.00004599535,0.00002946351,0.0002300476,0.9901561,0.0007648803,0.0003294378,0.008125421],"study_design_scores_gemma":[0.000006373218,0.0000480043,0.0003403796,0.000003924592,0.000006100013,0.0001344246,0.000009665351,0.004324429,0.9898379,0.0004807174,0.004798675,0.000009349042],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2553744,0.001840143,0.7285604,0.0009604351,0.0006780422,0.0001927366,0.0008785687,0.002103535,0.009411687],"genre_scores_gemma":[0.6110731,0.001772007,0.357758,0.0006819915,0.0002463073,0.0004253321,0.0009134875,0.0004013288,0.02672854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003389329,"threshold_uncertainty_score":0.01133841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02231681715137974,"score_gpt":0.3141510054066253,"score_spread":0.2918341882552456,"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."}}