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Record W2903820531 · doi:10.1139/cjp-2018-0522

Standardization of proton induced X-ray emission for analysis of trace elements in thick samples

2018· article· en· W2903820531 on OpenAlexvenueno aff
Johar Zeb, Shad Ali, Muhammad Haneef, Azhar Muhammad Naeem, Jehan Akbar

Bibliographic record

VenueCanadian Journal of Physics · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPelletronPhysicsProtonSpectral lineAnalytical Chemistry (journal)Tandem acceleratorBeam (structure)CopperTitaniumNuclear physicsMaterials scienceOpticsMetallurgyChemistry

Abstract

fetched live from OpenAlex

This paper presents the standardization of proton induced X-ray emission (PIXE) technique for the analysis of trace elements in thick, standard samples. Three standard reference materials, titanium, copper, and iron base alloys, were used for the study due to their availability. The proton beam was accelerated up to 2.57 MeV energy by 5UDH-II tandem Pelletron accelerator, and samples were irradiated at different geometries and durations. Spectra were acquired using a multi-channel spectrum analyzer, and spectra analyses were done using GUPIXWIN software for determination of elemental concentrations of trace elements. The obtained experimental data were compared with theoretical data and results were found to be in close agreement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.025
GPT teacher head0.302
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2018
Admission routes1
Has abstractyes

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