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Record W2577919954 · doi:10.1139/cjp-2016-0337

Determination of coherent to Compton scattering differential cross section ratios of some inorganic materials with EDXRF

2017· article· en· W2577919954 on OpenAlexvenueno aff
Demet Yılmaz, Ümit Şi̇mşek, Tuba Akkuş, Yücel Şahin

Bibliographic record

VenueCanadian Journal of Physics · 2017
Typearticle
Languageen
FieldMaterials Science
TopicRadiation Shielding Materials Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsCompton scatteringScatteringCross section (physics)Atomic physicsPhotonAbsorption cross sectionScattering cross-sectionGamma rayOpticsNuclear physics

Abstract

fetched live from OpenAlex

In this study, we aimed to determine coherent to Compton scattering differential cross section ratios of some inorganic materials (BaSO4, CaF2, Mg2SiO4, MgSO4, and ZnSO4(7H2O)) for several scattering angles (95°, 105°, 115°, 125°, and 135°). Coherent to Compton scattering differential cross section ratios were investigated experimentally by using an HPGe detector, which has a resolution of 199.6 eV at the 5.9 keV. The samples were excited with 59.54 keV gamma rays emitted from Am241 point source. The intensity ratios were corrected due to the photopeak efficiency of the gamma detector and absorption of photons in the target and air. It is observed that coherent to Compton scattering differential cross section ratios decrease with increasing scattering angle.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.259
Teacher spread0.242 · 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
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

Citations12
Published2017
Admission routes1
Has abstractyes

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