Properties of the Mangrove Community Sediment on the Island of El Souda Western Saudi Arabia
Bibliographic record
Abstract
Blue carbon refers to the carbon captured by oceans and coastal ecosystems. The carbon captured by living organisms in oceans is stored in the form of biomass and sediments. Blue carbon is considered to be a modern trend to reduce emissions of carbon dioxide in the atmosphere and mitigate climate change. The aim was to understand the characteristics and nature of this ecosystem. Data on various parameters including sediment hydro chemical properties, vital nutrients and organic matter were determined across eight different sectors that were divided on the basis of age and density of mangrove forest. The study showed that sectors in the studied mangrove forest of El-Souda–West Island Kingdom of Saudi Arabia with older and denser trees gave more significant information on hydro chemical properties than sectors with younger trees. Weak relationship was found between the degree of alkalinity and the growth of mangroves. The distribution of dissolved oxygen values was irregular between the sectors. The results of vital nutrients showed that the highest values of nitrates were recorded in sector 7 and 8. Absence of organic pollution in the study area that was attributed to organic rich sediment that gets accumulated in the mangrove roots. In general the values of vital nutrients below the international limit. A strong relationship was observed between the organic content of the sediment (organic carbon oxidized, organic carbon, total, organic matter), and the density of mangroves. The study revealed the role of benthic organisms especially cancers in enriching the sediment organic matter beside the impact of the tide, and the nature of the soil, and the proximity and distance from the sea.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".