Mesopotamian Marshlands: Salinization Problem
Bibliographic record
Abstract
Salinization becomes a very serious problem affecting the restoration assessment of the newly re-flooded marshes of the Mesopotamian southern Iraq. From mid-1970 to early-1990, the whole marsh area was influenced by water shortage and desiccation processes. Increasing the average salinity level in the re-flooded marshes is acting versus their recovery progress and significantly affecting their aquatic biota. This study will examine the contributions of dams’ construction and desiccation on increasing the salinity level with in the Mesopotamian marshlands overtime. Water discharge and salinity concentration were monitored in the direct water inputs and outlets of the three marshlands from May 2006 to February 2007 on a monthly basis, while salinity and major ions concentrations including “Ca1+, Mg2+, Cl1-, and SO42-” were monitored in 28 re-flooded marshes from March 2005 to August 2008 on a seasonal basis. The study indicate that increasing the salinity level in the Mesopotamian marshlands is due to three reasons: 1) The overtime increasing in the salinity level of their direct water inputs, due to dams’ constructions; 2) the increase of the Arab Gulf tide via Shatt Al-Arab river due to the reduction of the water level in the outlets of the Central and Al-Hammar marshlands; and 3) the huge accumulation of salts due to desiccation.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".