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Record W2984236326 · doi:10.1016/j.simpa.2019.100010

Peakaboo: Advanced software for the interpretation of X-ray fluorescence spectra from synchrotrons and other intense X-ray sources

2019· article· en· W2984236326 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSoftware Impacts · 2019
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsWestern University
FundersWestern Economic Diversification CanadaNatural Sciences and Engineering Research Council of CanadaCanadian HIV Trials Network, Canadian Institutes of Health ResearchUniversity of SaskatchewanNational Research Council CanadaCanarieCanada Foundation for InnovationOntario Centres of ExcellenceU.S. Department of Energy
KeywordsX-ray fluorescenceSoftwareSynchrotronSpectral lineTRACE (psycholinguistics)Synchrotron radiationInterpretation (philosophy)Sensitivity (control systems)Computer scienceFluorescenceAnalytical Chemistry (journal)PhysicsOpticsChemistryEngineeringEnvironmental chemistryElectronic engineering

Abstract

fetched live from OpenAlex

Peakaboo is a platform for the analysis of full spectrum synchrotron X-ray fluorescence (XRF) map data. It offers robust, automated fitting of XRF spectral peaks, increasing the sensitivity to trace chemical elements. Large arrays of spectral data can also be processed into element maps to define spatial relationships. The modifications to Peakaboo introduced since 2017 are particularly designed to help new users to become rapidly competent in the handling of complex XRF spectra. Some of the most important innovations of the software are described below. Finally, we share examples of its application in Earth and Environmental Sciences.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.008
GPT teacher head0.227
Teacher spread0.220 · 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