Optical Enhancing Properties of Anisotropic Gold Nanoplates Prepared with Different Fractions of a Natural Humic Substance
Bibliographic record
Abstract
The results of this work demonstrate the properties of suspensions of humic substances (HS) used as reducing and templating agent for the formation of gold nanostructures. It is further established that a considerable degree of control over the size and shape of the nanoparticles can be achieved by selecting the appropriate humic fraction and adjusting the pH of the working suspension. These gold nanostructures can sustain surface plasmon resonances and exhibit optical enhancing properties that make them suitable for plasmonic applications and optical enhancement such as surface-enhanced Raman scattering (SERS). The efficiency of the nanostructures as a SERS substrate is illustrated enhancing the Raman spectrum of 2-mercaptobenzothiazole (MBT), a common organic pollutant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".