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Record W3148733365

Perchlorate and Nitrate in Leafy Vegetables of North America

2005· article· en· W3148733365 on OpenAlexaboutno aff
C. A. S Anchez, Rigomar Rieger, N. R. K Handaker, J. P. G Ibbs

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicChemical Analysis and Environmental Impact
Canadian institutionsnot available
Fundersnot available
KeywordsPerchlorateNitrateLactucaLeafy vegetablesEnvironmental scienceChemistryToxicologyAgronomyFood scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

| In previous studies trace levels of perchlorate were found in lettuce (Lactuca sativa L.) irrigated with Colorado River water, which is contaminated with low levels of perchlorate from aerospace and defense related industries. In this paper, we report the results of a survey conducted across North America to evaluate the occurrence of perchlorate in leafy vegetables produced outside the lower Colorado River region, and evaluate the relative iodide uptake inhibition potential to perchlorate and nitrate in these leafy vegetables. Conventionally and organically produced lettuce and other leafy vegetable samples were collected from production fields and farmers' markets in the central and coastal valleys of California, New Mexico, Colorado, Michigan, Ohio, New York, Quebec, and New Jersey. Results show that 16% of the conventionally produced samples and 32% of the organically produced samples had quantifiable levels of perchlorate using ion chromatography. Estimated perchlorate exposure from organically produced leafy vegetables was approximately 2 times that of conventional produce, but generally less than 10% of the reference dose recommended by the National Academy of Sciences. Furthermore, the iodide uptake inhibition potential of perchlorate was less than 1% of that of the nitrate present. These data are consistent with those of other reported perchlorate survey work with lettuce, bottled water, breast milk, dairy milk, and human urine, and suggest a wide national presence of perchlorate.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.000

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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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 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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