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Record W4289783983

Meta-analysis of environmental contamination by phtalates

2013· preprint· en· W4289783983 on OpenAlexaboutno aff
Alexandre Bergé, Mathieu Cladière, Johnny Gaspéri, Bruno Tassin, Régis Moilleron, Annie Coursimault

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2013
Typepreprint
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsContaminationEnvironmental scienceBiologyEcology
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Phthalate Acid Esters (PAE), commonly named Phthalates, are toxics classified as endocrine-disrupting compounds; they are primarily used as additives to improve the flexibility in polyvinyl chloride. Occurrence: Many studies have reported the occurrence of phthalates in different environmental matrices, however none of these studies has yet establish a complete overview for those compounds in the water cycle within an urban environment. This review summarizes PAE concentrations for all environmental media throughout the water cycle, from atmosphere to receiving waters. Once the occurrences of compounds have been evaluated for each environmental compartment (urban wastewater, wastewater treatment plants, atmosphere and the natural environment), data are reviewed in order to identify the fate of PAE in the environment and establish whether geographical and historical trends exist. Indeed, geographical and historical trends appear between Europe and other countries such as USA/Canada and China, however they remain location-dependent. Discussion: This study aimed at identifying both the correlations existing between environmental compartments and the processes influencing the fate and transport of these contaminants into the environment. In Europe, the concentrations measured in waterways today represent the background level of contamination, which provides evidence of a past diffuse pollution. In contrast, an increasing trend has actually been observed for developing countries, especially for China.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.000

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 head0.031
GPT teacher head0.243
Teacher spread0.212 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

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