MétaCan
Menu
Back to cohort
Record W4313420518 · doi:10.1016/j.chroma.2022.463717

Determination of distribution coefficients of mercury and gold on selected extraction chromatographic resins - towards an improved separation method of mercury-197 from proton-irradiated gold targets

2022· article· en· W4313420518 on OpenAlexafffund
Shaohuang Chen, Marine Bas, Steffen Happel, Parmissa Randhawa, Scott McNeil, Elena Kurakina, Stefan Zeisler, Keiran Maskell, Cornelia Hoehr, Caterina F. Ramogida, Valery Radchenko

Bibliographic record

VenueJournal of Chromatography A · 2022
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of VictoriaSimon Fraser UniversityTRIUMF
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCanadian Cancer Society
KeywordsChemistryMercury (programming language)ChromatographyInductively coupled plasma mass spectrometryIrradiationMass spectrometryAnalytical Chemistry (journal)Radiochemistry

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
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 score0.143
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.017
GPT teacher head0.346
Teacher spread0.328 · 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

Citations14
Published2022
Admission routes2
Has abstractno

Explore more

Same venueJournal of Chromatography ASame topicRadiopharmaceutical Chemistry and ApplicationsFrench-language works237,207