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Record W805960710

Analytical method of PCDDs/PCDFs in blood using NIST SRM 1589a

2005· article· en· W805960710 on OpenAlexaboutno aff
Sun Kyoung Shin, Seok Un Park, Tae Seung Kim

Bibliographic record

VenueAnalytical Science and Technology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
Fundersnot available
KeywordsNISTChromatographyChemistryCalibrationAnalytical Chemistry (journal)Detection limitCalibration curveEnvironmental scienceMathematicsComputer scienceStatistics
DOInot available

Abstract

fetched live from OpenAlex

For the analytical method of PCDD/Fs in blood, which have been issued recently, SRM 1589a of NIST(National Institute of Standards and Technology) was used and a practical analytical method of PCDD/Fs in blood was presented through comparison of methods of Canada and Japan. The proposed method used alkali-digestion extraction for removal of the lipid effectively using two capillary columns. The limit of quantification of TeCDD/DF and PeCDD/DF was 1 pg/g-lipid, HxCDD/DF and HpCDD/DF was 2 pg/g-lipid, OCDD/DF was 4 pg/g-lipid. With consideration the range of detected concentration, calibration standards were presented as (0.1~1), (0.25~2.5), (0.5~5.0), (2~20), (10~100).

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.309
Teacher spread0.293 · 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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