The effect of the water column on submerged coral reef hyperspectral response
Bibliographic record
Abstract
Monitoring coral reef ecosystems systematically and repetitively using remote sensing technology will help document the scale, extent and duration of ecosystem changes. A satellite or airborne image could be used to create a thematic map delineating areas where corals are under stress and would enable change detection studies to determine the extent and rate of coral health decline or recovery. One limitation to the accuracy of interpreting uncorrected images of submerged ecosystems is that the water column over a submerged coral reef modifies the remotely sensed signal within the visible spectrum. Furthermore, the effect has been observed as depth, bottom-type, and wavelength dependent; such complex modifications limit the accuracy of remote identification of submerged coral reef features. In an attempt to resolve this problem, in situ hyperspectral reflectance measurements were collected in the U.S. Virgin Islands at various depths, over different substrate types in water of consistent quality. A comparison is made between top and bottom of the water column hyperspectral reflectance in different water depths over different substrate types.
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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 | 0.000 | 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 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".