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Las dudas del Big Data

2014· article· en· W20378154 on OpenAlexaboutno aff
Pablo Albarracín, David Cornejo

Bibliographic record

VenueAmérica economía · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Assessment of organochlorine pesticides (OCPs) in human body is important for human health because they have weak estrogenic or antiestrogenic effects and are considered endocrine disrupters. We used colostrum of women as indicator for levels of OCPs in human body for mothers with normal and preterm labor from eastern part of Romania. Sixty- three samples of colostrum were extracted by solid-phase extraction. Analyses were carried out using gas chromatography coupled to mass spectrometry (GC-MS). OCPs have been detected in all samples, with p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) and gamma-hexachlorocyclohexane (gamma-HCH) being at the highest concentrations. Of the organochlorines measured in clostrum samples from women in preterm labor, median levels of DDTs (470 ng/g) and HCHs (99 ng/g) were higher than for the same compounds from women in normal labor (median of DDTs=268 ng/g and median of HCHs=96 ng/g). Normal labor had higher median concentrations of HCB (19.5 ng/g) versus preterm labor (14 ng/g). Statistical data show high Spearman correlation coefficients between various OCPs. We found a good correlation between alpha-, gamma-, beta- and delta- HCH isomers (p<0.001) for both normal and preterm labor. The most abundant target compound was p,p'-DDE (median value 96 ng/g, and 137 ng/g for mother with normal and preterm labor, respectively) in all colostrum samples. The estimated daily intakes of HCHs by infants exceeded corresponding Health Canada guidelines.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.757
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.008

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 head0.112
GPT teacher head0.224
Teacher spread0.113 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2014
Admission routes1
Has abstractyes

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