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Record W3172051999 · doi:10.1093/chromsci/bmab076

HPTLC Method for the Ultrasensitive Detection of Triamterene in Plasma

2021· article· en· W3172051999 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Chromatographic Science · 2021
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChromatographyChemistryTriamtereneHuman plasmaHydrochlorothiazide

Abstract

fetched live from OpenAlex

A high-performance thin-layer chromatographic (HPTLC) method has developed for the selective detection of a diuretic drug, triamterene (TRIAM), in pure form, tablets and human plasma. The method was based on chromatographic separation of TRIAM using HPTLC plates, precoated with silica gel, and a mobile phase consisted of ethyl acetate: dimethylformamide: ammonia (7.0: 2.7: 0.3, by volume). The native fluorescence signal of TRIAM was detected at 440 nm and used to quantify TRIAM using the proposed method, improving the method sensitivity to ~250-folds in comparison to that reported in previous HPTLC studies. The developed method enabled the detection of TRIAM in pure drug and biological samples (human plasma) within linear concentrations ranged from 0.8 to 60 ng/band or 1.0 to 60 ng/band for pure drug and plasma samples, respectively. Furthermore, the method was validated according to the official guidelines to permit its applicability in quality control and clinical laboratories.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.288
Teacher spread0.275 · 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