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Record W2164846742 · doi:10.1039/b314732k

Analysis of pharmaceutical tablets by laser ablation inductively coupled plasma atomic emission spectrometry and mass spectrometry (LA-ICP-AES and LA-ICP-MS)Electronic supplementary information (ESI) available: images of the ablation craters and trenches in the tablets. See http://www.rsc.org/suppdata/ja/b3/b314732k/

2004· article· en· W2164846742 on OpenAlexafffund
Rebecca Lam, Eric D. Salin

Bibliographic record

VenueJournal of Analytical Atomic Spectrometry · 2004
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMass spectrometryChemistryInductively coupled plasma atomic emission spectroscopyAnalytical Chemistry (journal)Detection limitInductively coupled plasma mass spectrometryInductively coupled plasmaLaser ablationChromatographyLaserPlasma

Abstract

fetched live from OpenAlex

Laser ablation was studied with inductively coupled plasma atomic emission spectrometry (LA-ICP-AES) and with inductively coupled mass spectrometry (LA-ICP-MS) for the analysis of pharmaceutical tablets (10% and 20% Neusilin). For spot analysis with LA-ICP-AES, precision ranged from 12–31% relative standard deviation (RSD), but improved to 1–6% when ratios of signals were used. For continuous scanning, the precision ranged from 1–7% RSD. Weaker laser conditions required for ICP-MS gave precisions of 47–61% RSD (29% when signal ratios were used). Under unoptimized conditions, the detection limits for LA-ICP-AES of tablets were 70 µg g−1 for Al and 20 µg g−1 for Mg. The detection limits for LA-ICP-MS were 40 µg g−1 for Al and 6 µg g−1 for Mg. These results suggest that LA-ICP spectroscopy may find application in tablet analysis.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
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 teacher head, not a consensus.

Study designBench or experimental
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

Citations21
Published2004
Admission routes2
Has abstractyes

Explore more

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