Assessing the Gold Standard: The Complex Vibrational Nonlinear Susceptibility of Metals
Bibliographic record
Abstract
Sum-frequency generation techniques can offer molecular-level, structural details of surfaces and interfaces. The incorporation of a metallic layer, either exposed or buried, is frequently used to provide a nonvibrationally resonant reference to which the phase of the resonant responses may be compared. This in turn provides further structural information, such as the polarity of interfacial groups. Because the phase of the metal depends strongly on factors that alter the electronic structure of the interface, such as the wavelength of the visible beam, chemical bonding, and surface coverage, it is beneficial to characterize the phase of the nonresonant response. A direct measurement of the absolute phase of a commonly prepared model hydrophobic surface, 1-octadecanethiol bound to gold, is presented and compared with relative phase measurements. Assignment of the phase of metallic samples requires careful consideration of the effects of the local field upon phase in both the near and far fields. We have outlined an approach that is suitable for the characterization of any dielectric or metal surface.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".