The Environmental Impact of Urbanization within Abu Dhabi on the Microbial Profile of Man-Made Beaches
Bibliographic record
Abstract
The United Arab Emirates (UAE) is witnessing a significant development in several areas. Many new construction projects are currently underway. One of the main project aims at establishing new beaches around the coastal areas of the UAE. Particularly, in Abu Dhabi the capital of UAE, a new man-made beach has been recently developed in the north coast of the city. The urbanization of this newly developed beach might have a significant impact on the environment. This study aims to investigate the effects of urban development of beaches within Abu Dhabi on the microbial profile of the soil. It is hypothesized that microbial growth would be higher in man-made beaches as compared to natural beaches. Methodology involved collection of 16 soil samples from two different beaches with emphasis on two elements: water content in soil and depth of soil. Subsequently, samples were processed and used for microbial cultivation using selective and differential growth media for the identification of some commonly encountered microorganisms namely "yeast, faecal coliforms, Escherichia coli and Staphylococcus aureus". Polymerase Chain Reaction (PCR) and electrophoresis were also used for further analysis. Results of the study revealed the existence of Staphylococcus aureus, Escherichia. coli and coliforms in the soil samples isolated from the man-made beach. Moreover, the hypothesis was supported by the results which showed higher microbial growth (CFU/g) for both factors: (depth of the soil and water content) for man-made beaches as compared to natural beaches.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".