Reflectance versus transmittance: The effects of light scattering on red colorants (carmine, amazonian red annatto, and peruvian cochinilla rojo and rosada) in biological, textile, and museum science
Bibliographic record
Abstract
Abstract Spectra were strongly influenced by the way they were measured but, in general, carmine, cochinilla rojo and rosada, and red annatto all had strong transmittance and reflectance of red light (>640 nm), and strong absorbance of green light (520–560 nm). Spectra for carmine and cochinilla rosada both had secondary peaks for transmittance and reflectance (around 420 and 450 nm for stains, respectively), whereas secondary peaks were not found for cochinilla rojo and red annatto. Both cochinilla rosada and rojo stained skeletal myofibers, but only cochinilla rojo withstood alcohol dehydration and mounting as a general stain for paraffin sections. Carmine was ideal for enhancing the appearance of pork because its spectrum was similar to that of myoglobin, thus increasing the absorbance of green light without producing unnatural colors like cochinilla rosada and rojo. Cochinilla rojo dyed alpaca wool orange, and cochinilla rosada dyed wool pink. The scale of the measurement (micro‐ vs. macroscopic) and the type of measurement (transmittance vs. reflectance) were of minor importance in colorimetry, whereas a major effect was detected for light scattering in the sample. A ratio indicative of scattering (400/700 nm) was strongly correlated with chromaticity coordinate x, r = −0.86, P < 0.001, n = 18. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 599–606, 2014
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".