MétaCan
Menu
Back to cohort
Record W2315182379 · doi:10.1097/mnm.0000000000000108

A sensitive, rapid and inexpensive method to assess aluminium(III) ions in technetium eluates

2014· article· en· W2315182379 on OpenAlexaff
Federica Eleonora Buroni, Lorenzo Lodola, Marco Giovanni Persico, C. Aprile

Bibliographic record

VenueNuclear Medicine Communications · 2014
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging and Pathology Studies
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsChemistryDetection limitAluminiumFilter paperChromatographyReagentAnalytical Chemistry (journal)Nuclear chemistry

Abstract

fetched live from OpenAlex

The aim of the study was to validate a semiquantitative analytical method to identify the aluminium(III) [Al(III)] concentration in 99Mo/99mTc generator eluates to check the European Pharmacopoeia (Ph. Eur.) requirement (<5 μg/ml). Three different solutions measuring 20 ml - 0.2% 1,10-phenanthroline, 0.05% chrome azurol S and 20% hexamethylenetetramine - were prepared. A cellulose filter paper was subsequently immersed in them, dried overnight at room temperature and cut into rectangles. A volume of 5 μl of first eluates of various 99Mo/99mTc generators was placed onto a reagent paper and the spot colour was compared with a standard aluminium solutions scale (0-100 μg/ml). A cyan/magenta/yellow/key (CMYK) model analysis was adapted to quantify the intensity of colour on the paper, and the presence of aluminium in the eluates was detected by a spectrophotometer. Small changes in standard solution pH (4.1-5.2) and chrome azurol S concentration did not affect the analysis. The cyan channel image analysis was proportional to the Al3+ solution concentration (y=25 019x+1489, R2=0.9554 within 2.5-8 μg/ml). The detection limit for aluminium by the visual test method is about 1 μg/ml, and fading is absent. The cyan channel image analysis method is independent of the observer and is applicable for the evaluation of the chemical purity of 99Mo/99mTc generator eluates. Our colorimetric 'spot test' is advantageous for the visual evaluation of Al pertechnetate concentrations as required by Ph. Eur. showing a sensitivity and a limit of detection superior to that of commercially available spot systems.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.773
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.102
GPT teacher head0.402
Teacher spread0.300 · 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 designNot applicable
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

Citations1
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueNuclear Medicine CommunicationsSame topicMedical Imaging and Pathology StudiesFrench-language works237,207