Surface-enhanced resonance raman scattering (SERRS) using Au nanohole arrays on optical fiber tips
Bibliographic record
Abstract
Agradecimentos: This work was supported by operating grants from NSERC and by the NSERC Strategic Network for Bioplasmonic Systems (BiopSys), Canada. The equipment grant was provided by the Canada Foundation for Innovation, the British Columbia Knowledge and Development Fund, and the University of Victoria through the New Opportunities Program. The Brazilian authors thank FAPESP for financial support. The authors thank the Centro de Componentes Semicondutores—UNICAMP for the use of the FIB facility and Antônio Von Zuben, from the Laboratório de Pesquisa de Dispositivos—UNICAMP, for metal coating optical fibers. G.F.S.A. thank the Canadian Bureau for International Education—Department of Foreign Affairs and International Trade of Canada for a post-doctoral fellowship. WJC thank Prof. Reuven Gordon, from the Department of Electrical Engineering at the University of Victoria, for providing access to the Lumerical software
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".