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Record W2756951784 · doi:10.1039/c7em00278e

Variations in serum concentrations of selected organochlorines among delivering women in Argentina. The EMASAR study

2017· article· en· W2756951784 on OpenAlexaff
Solrunn Hansen, Evert Nieboer, Natalia Bravo, Inger Økland, Silvinia Matiocevich, Marisa Viviana Alvarez, Stein Tore Nilsen, Joan O. Grimalt, Jon Øyvind Odland

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEnvironmental healthSerum concentrationEnvironmental scienceEnvironmental chemistryGeographyMedicineChemistryInternal medicine

Abstract

fetched live from OpenAlex

lipid, p = 0.022). Age was generally associated positively with the body burden of nearly all OCs and parity negatively so, with p,p'-DDD, o,p'-DDT, and o,p'-DDD residues and α-HCH in Ushuaia being the exceptions. The regional differences in OC concentrations are explained by contrasting domestic sources, historical and current uses, industrial emissions, dietary patterns and lifestyle factors, as well as long-range-transport. The relatively high PCB 118/PCB 180 ratio observed for both Argentinian communities likely reflects the use of technical mixtures with congener-specific composition. In a comprehensive comparison with other countries, the Argentinian OC concentrations were mostly in the lower range. It is concluded that a latitude effect equivalent to that operative in the Arctic region seems unlikely.

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)0.001
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 score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.240
Teacher spread0.232 · 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

Citations8
Published2017
Admission routes1
Has abstractyes

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