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Record W7038605691

Impact des émissaires et canalisation sur l'environnement de la baie de Tanger ( Maroc ) : Approche géochimique.

2005· article· en· W7038605691 on OpenAlexfundno aff

Bibliographic record

VenueAquaDocs (United Nations Educational, Scientific and Cultural Organization) · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersCentre National pour la Recherche Scientifique et TechniqueCanadian Academy of Sport and Exercise Medicine
KeywordsBaySedimentOrganic matterSedimentary rockPollutionHydrology (agriculture)ContaminationTotal organic carbon
DOInot available

Abstract

fetched live from OpenAlex

Several samples collected from two main rivers (Souani and Mghogha) and the largest pipeline of Tangier’s city that pours into Tangiers bay (Mediterranean Moroccan margin), were analysed with the objective of evaluating the chemical and/or organic contamination degree of superficial sediments present along these continental emissaries. The sedimentary dynamics of these rivers show coarsening upstream evolution, influenced by the urban and industrial liquid and solid discharges (infilling basin side with building materials such a bricks, cement, glass, etc.). Organic matter is present with high concentration, showing a positive correlation with the sediment fine fraction. Total Nitrogen displays a parallel evolution with the organic matter, with especially high concentrations near the urban sewage. The six heavy metals analyzed in the superficial sediments, show variable but relatively high concentrations, mainly in the fine fraction, with Zn < Cr < Pb < Ni < Cu < Cd. The correlative study of these metallic elements prove their double anthropogenic and natural origin.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.108
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.280
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2005
Admission routes1
Has abstractyes

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