Effects of river sediments on coral recruitment, algal abundance benthic community structure on Kenyan coral reefs
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
The effects of sediment concentration and season on coral recruitment algal abundance and benthic community structure were studied in Kenyan coral reef lagoons to determine their potential influence on coral recovery. Nutrient levels and recruit numbers were higher during the southeast monsoon (SEM) than during the northeast monsoon (NEM) season and in sediment-exposed compared to non-sediment exposed reefs. Mean algal biomass also exhibited the same seasonal trend (except at one site), but was higher in the non-sediment exposed reef compared to the other reefs. Corals in the sediment exposed reef exhibited morphological differences relative to the other reefs: fewer corymbose and plate-like but more branching, massive and solitary forms and increased colony and corallite sizes. However, sediments did not suppress coral recruitment rates. These morphological changes coupled with the interaction between biological and physico-chemical characteristics have important ecological and geological implications: by potentially modifying calcium carbonate production and ameliorating the adverse effects of climate induced stress events, this may minimize coral mortality and enhance reef recovery. Key words: Algal biomass, coral recruitment, hydrodynamics, coral morphology, seasonality, sediments.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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