Methodology for computing Fourier-transform infrared spectroscopy interferograms
Bibliographic record
Abstract
With the utilization of Fourier-transform infrared (FTIR) spectroscopy for a multitude of commercial applications, a robust methodology for designing, implementing, and servicing these systems in commercial settings is becoming increasingly paramount. Here we present a method allowing for the numerical evaluation of the interferogram signal in a FTIR spectroscopy system, in which the incident electric field can exhibit any arbitrary spectral content. The developed model assesses multiple internal reflections occurring within a beam splitter (BS) and compensating plate (CP), allows for the presence or absence of the CP, and obtains the interferogram in absolute units. The interferogram is evaluated for the representative scenarios of an incident electric field having a blackbody spectral distribution (interacting with a BS and CP composed of SiO 2 ) and a randomly chosen spectral distribution (interacting with a BS composed of ZnSe and no CP).
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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) | 0.000 | 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".