Datasets of trace elements in shallow marine sediments along the Egyptian shore of the Mediterranean and Red Seas
Bibliographic record
Abstract
A comprehensive dataset concerning the geochemical composition of unconsolidated shallow marine sediments collected along coastal areas of Northern Nile Delta and Egyptian sector of Red Seas is presented. The sediment samples were analyzed using instrumental neutron activation analysis (INAA) in Frank Laboratory of Neutron Physics FLNP - Joint Institute for Nuclear Research JINR and inductively coupled plasma - mass spectrometer (ICP-MS) in Actlabs - Canada. Data thus collected supported the research published and published articles conducted to evaluate the geochemistry of shallow marine sediments covering mentioned areas [1], [2], [3]. The mass fractions of 43 and 39 trace elements and oxides were determined in the unconsolidated marine sediments of Northern Nile Delta and Egyptian sector of Red Sea, respectively. Final data were expressed in wt.% and mg/kg for major and trace elements, respectively. Different statistical tests such as Shapiro-Wilk, Anderson-Darling, Lilliefors and Jarque-Bera were used to check the normality of data. At the same time, distribution patterns of the rare earth elements (lanthanides) as well as Eu and Ce anomalies were investigated. Quality control of analytical measurements was carried out using certified reference materials. Different univariate and multivariate as well as graphic statistical analyses were performed. Presented data were used in identifying, by means of more pollution indices, the degree of local contamination. The present dataset could be further used in establishing geochemical background for the studied areas and tracking eventually changes posing significant threat to environment and humans.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".