Hyperspectral linear mixing based on in situ measurements in a coral reef environment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the benthic complexity common on a coral reef, there will always be subpixel mixing given the spatial resolution of contemporary satellite imagery. It therefore becomes important to determine how spectral components of a pixel combine to result in one integrated pixel value. To address this issue, pure endmember high spectral resolution measurements were taken in Buck Island Marine Park, off St. Croix, U.S. Virgin Islands. Linear spectral mixing was used with these endmember spectra (coral, sand, grass, bleached coral, and benthic algae) to examine the integrated pixel signals. Results indicate that when the sand component of the mixed spectra is only 25%, there is a notable increase in magnitude of reflectance. Cluster analyses of end member spectra and mixed spectra indicate that a relatively small sand component within a mixed pixel will effectively dominate the pixel's spectral signal. The spectral signal of a pixel with only 25% sand cover lacks similarity to other endmembers present, retaining spectral characteristics specific to sand, with significant implications for image analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it