Exposure at low tide leads to a different microbial abundance of intertidal coral <i>Acropora pulchra</i>
Bibliographic record
Abstract
Abstract Corals thrive in symbiotic relationships with a variety of microorganisms, including endosymbiont algae. The interaction between coral and microbial associations has been extensively researched since it is thought to play a function in coral health. Temperature and light are two abiotic elements that contribute to coral life. Corals in reef flat environments frequently face variations in these two characteristics due to their proximity to shallow seas. This study aims to compare the microbial diversity and abundance associated with the coral Acropora pulchra on the reef flat under two conditions, namely corals that emerged to the surface at low tide (SF) and corals that submerged over time (SM) and to compare the microbial diversity of both with those found in its adjacent seawaters. Microbial analysis on 16S rRNA region V4 showed that the alpha diversity of coral microbial communities and seawaters was not significantly different. However, differences in abundance were noticed at the phylum and genus levels. With p-value < 0.05, PCoA analysis using the Bray-Curtis test showed that the coral microbial community was significantly different from the surrounding seawaters. This study indicates that, under different conditions, corals of the same species can be dominated by different microbial groups and confirms the uniqueness between coral microbes and its adjacent seawaters. The abundance of certain microbes is a host mechanism for survival.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".