Pearl Oyster: From National Icon To Guardian of Qatar's Marine Environment
Bibliographic record
Abstract
The NPRP9-394-1-090 project “Pearl Oyster: from national icon to guardian of Qatar's marine environment” had as main aim to develop and apply an integrated suite of chemical and biological methods as early warning tools to assess the “health” of Qatar’s marine environment. The central theme consisted in an investigative monitoring program around the use of the pearl oyster, Pictada imbricata radiata, as a sentinel or guardian species. We have characterized the main environmental contaminants of concern at a selected number of sites around the Qatari coast (UmmBab, Al Khor, Al Wakra and Simaisma), during 2 years, in summer and winter. Potential ecological effects of contaminants (targeted and untargeted) were investigated at different biological organization levels (gene, chromosome, cell, individual, population), through a multidisciplinary approach, using classical and genotoxicological endpoints, integrative histopathology and transcriptomic responses to the different environmental stresses. To our knowledge, this is the first time an integrated approach connecting all these disciplines has been applied in the Qatari marine environment. We present here the main results, of this 3 years project, obtained in all different disciplinary approaches. The results of this project will leave a legacy of resources for future Qatari researchers, including an open access transcriptome data base and the first description of common pathologies observed in the pearl oyster P. i. radiata. Moreover, they will also represent a sound science-based baseline data essential for conservation and management planning, by integration of the data from all the different disciplines applied in the project to assess the potential ecological effects of contaminants at different biological levels.
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.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".