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Record W6998904888

Assessment of Douro and Ave River (Portugal) lower basin water quality focusing on physicochemical and trace element spatiotemporal changes

2018· article· en· W6998904888 on OpenAlexaboutno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsEstuaryWater qualityHydrology (agriculture)Trace elementDrainage basinNitrateNutrientSampling (signal processing)
DOInot available

Abstract

fetched live from OpenAlex

Water quality of Douro and Ave lower basin was evaluated regarding physicochemical parameters (pH, conductivity, dissolved oxygen and temperature), nutrient compounds (nitrates, nitrites, ammonium and orthophosphates), chlorophyll a and occurrence of trace elements (Li, Be, Al, Ti, V, Cr, Co, Ni, Cu, Zn, Se, Mo, Ag, Cd, Sb, Ba, Tl, Pb, Th and U). To study spatiotemporal variations and possible anthropogenic sources, estuarine samples were collected at nine sampling sites in Douro and five in Ave distributed along the estuaries at four sampling campaigns (spring, summer, fall and winter). According to the water quality standards for aquatic life and recreation, Douro and Ave river water quality was found out of safe limits regarding several parameters. Nitrate levels were systematically high (> 50 mg L−1 in a significant number of samples) and mean levels of trace elements were higher than the established values of Canadian Environmental Quality Guidelines for aquatic life protection for Al, Cu, Se, Ag, Cd and Pb in Douro and Ave, and also Zn in Ave. Significant spatial differences were found in Ave river estuary for trace elements with a clear trend for higher values from upstream to downstream found. Seasonal differences were also observed particularly in Douro river estuary with higher levels in spring for most elements. © 2018, © 2018 Taylor & Francis Group, LLC.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.089
GPT teacher head0.410
Teacher spread0.320 · 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.

Study designBench or experimental
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
Published2018
Admission routes1
Has abstractyes

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