MétaCan
Menu
Back to cohort
Record W2152838775 · doi:10.1002/jssc.200800337

Determination of pharmaceuticals in drinking water by CD‐modified MEKC: Separation optimization using experimental design

2008· article· en· W2152838775 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 Separation Science · 2008
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsChemistryChromatographyDetection limitNaproxenPropylparabenAnalyteKetoprofenFlumequineEnrofloxacin

Abstract

fetched live from OpenAlex

A suite of 12 widely used pharmaceuticals (ibuprofen, diclofenac, naproxen, bezafibrate, gemfibrozil, ofloxacin, norfloxacin, carbamazepine, primidone, sulphamethazine, sulphadimethoxine and sulphamethoxazole) commonly found in environmental waters were separated by highly sulphated CD-modified MEKC (CD-MEKC) with UV detection. An experimental design method, face-centred composite design, was employed to minimize run time without sacrificing resolution. Using an optimized BGE composed of 10 mM ammonium hydrogen phosphate, pH 11.5, 69 mM SDS, 6 mg/mL sulphated beta-CD and 8.5% v/v isopropanol, a separation voltage of 30 kV and a 48.5 cm x 50 microm id bare silica capillary at 30 degrees C allowed baseline separation of the 12 analytes in a total analysis time of 6.7 min. Instrument LODs in the low milligram per litre range were obtained, and when combined with offline preconcentration by SPE, LODs were between 4 and 30 microg/L.

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)0.000
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 score0.473
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.089
GPT teacher head0.382
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