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Record W3111248282 · doi:10.1063/5.0032164

Sediment natural radioactivity and heavy metals assessment from the beaches of Ras-Gharib, Red Sea, Egypt

2020· article· en· W3111248282 on OpenAlexaboutno aff
Mostafa Y. A. Mostafa, Hesham M.H. Zakaly, M.A.M. Uosif, Sh. A. M. Issa, Hashem A. Madkour, Mahmoud Tammam

Bibliographic record

VenueAIP conference proceedings · 2020
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsTerrigenous sedimentHeavy metalsSedimentAtomic absorption spectroscopyEnvironmental sciencePollutionEnvironmental chemistryNatural radioactivityExtraction (chemistry)ChemistryGeologyRadionuclideGeomorphology

Abstract

fetched live from OpenAlex

Natural 238U, 232Th and 40K activity in sediment samples from beaches along Ras-Gharib coast on the Red Sea, Egypt has been estimated. Eighteen sediment samples from 3 beaches were collected and measured with Nal (Tl) gamma spectrometry. The average specific activities are 28 ±1.9, 24±2.8, and 382±21.4 Bqkg−1 for 238U, 232Th and 40K, respectively. These values are less than the worldwide average of 33, 45, and 412 Bq kg−1 recommended by UNSCEAR reports. Absorbed dose rate the annual effective dose are calculated 34 nGyh−1 and 42 µSvy−1 respectively. Eight heavy metals (Fe, Mn, Ni, Co, Zn, Cu, Pb and Cd) have been measured and analyzed by atomic absorption spectrometer (AAS). ln some samples, the concentration for the investigated heavy metals exceeds the permissible limits recommended by the Canadian Environmental Quality Guidelines. This indicated that the degree of metals pollution is caused by anthropogenic activities (Terrigenous sediments transported to the marine environment by some wadis in the General Beach area, oil spills as a result of exploration and extraction in General Company of Petroleum) and/or by natural impacts.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.118
GPT teacher head0.368
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2020
Admission routes1
Has abstractyes

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