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Record W2036042525 · doi:10.1002/elps.200500832

Interlaboratory study of a NACE method for the determination of <b><i>R</i></b>‐timolol content in <b><i>S</i></b>‐timolol maleate: Assessment of uncertainty

2006· article· en· W2036042525 on OpenAlexaff
R.D. Marini, Carl A. Groom, François R. Doucet, Jalal Hawari, Yaser Bitar, Ulrike Holzgrabe, Roberto Gotti, Julie Schappler, Serge Rudaz, Jean‐Luc Veuthey, Roelof Mol, Govert W. Somsen, Gerhardus J. de Jong, Phạm Thị Thanh Hà, Jie Zhang, Ann Van Schepdael, Jos Hoogmartens, Willy Briône, Attilio Ceccato, Bruno Boulanger, Debby Mangelings, Yvan Vander Heyden, Willy Van Ael, Ilias Jimidar, Matteo Pedrini, Anne‐Catherine Servais, Marianne Fillet, Jacques Crommen, Eric Rozet, Philippe Hubert

Bibliographic record

VenueElectrophoresis · 2006
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsBiotechnology Research Institute
Fundersnot available
KeywordsTimololRepeatabilityReproducibilityChromatographyChemistryReplicateMathematicsStatisticsAnalytical Chemistry (journal)MedicineIntraocular pressureOphthalmology

Abstract

fetched live from OpenAlex

Analyses of statistical variance were applied to evaluate the precision and practicality of a CD-based NACE assay for R-timolol after enantiomeric separation of R- and S-timolol. Data were collected in an interlaboratory study by 11 participating laboratories located in Europe and North America. General qualitative method performance was examined using suitability descriptors (i.e. resolution, selectivity, migration times and S/N), while precision was determined by quantification of variances in the determination of R-timolol at four different impurity levels in S-timolol maleate samples. The interlaboratory trials were designed in accordance with the ISO guideline 5725-2. This allowed estimating for each sample, the different variances, i.e. between-laboratory (s2(Laboratories)), between-day (s2(Days)) and between-replicate (s2(Replicates)). The variances of repeatability (s2r) and reproducibility (s2R) were then calculated. The estimated uncertainty, derived from the precision estimates, seems to be concentration-dependent above a given threshold. This example of R-timolol illustrates how a laboratory can evaluate uncertainty in general.

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 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 score0.009
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.294
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations24
Published2006
Admission routes1
Has abstractyes

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