Determining recovery success in Anthelia sp. after exposure to varying levels of thermal stress
Bibliographic record
Abstract
Coral bleaching is a phenomenon caused by anthropogenically increased ocean temperatures, and may lead to the eventual death of massive reef systems. Bleaching is the result of corals expelling dinoflagellate endosymbionts in order to compensate for thermal stress. However, the loss of symbionts leads to a subsequent reduction in fluorescence intensity emitted by the coral. Substantial research has been done on coral bleaching due to environmental stressors, but little knowledge has been acquired about coral recovery after thermal stress. The present study aimed to determine how Anthelia species recover after being exposed to varying levels of temperature stress. Corals were exposed to varying levels of heat stress and subsequently brought back down in temperature to promote recovery. Using fluorescence microscopy, a relatively new method of quantifying coral health, and health-colour indices, recovery ability after thermal stress was determined. Analyses concluded that corals were able to successfully recover after thermal stress of 31°C, and exhibit a thermal compensation point around 30°C. However, beyond 31°C, recovery was not achievable. The findings of this study are beneficial to the larger coral research field because they indicate that corals do possess recovery ability up until reaching a fatal thermal maximum.
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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 | 0.001 |
| 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".