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Record W2315413793 · doi:10.1063/1.3000661

Cross-section measurements of the N14(α,p)O17 and N14(α,α)N14 reactions between 3.5 and 6 MeV

2008· article· en· W2315413793 on OpenAlexaff
G. Terwagne, Géraldine Genard, M. Yedji, G.G. Ross

Bibliographic record

VenueJournal of Applied Physics · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsNitrogenNuclear reaction analysisSiliconNuclear reactionChemistryTinAnalytical Chemistry (journal)Cross section (physics)RadiochemistryAtomic physicsIonEnvironmental chemistry

Abstract

fetched live from OpenAlex

The cross-section of the N14(α,p0)O17 reaction at angles of 90°, 135°, and 165° was measured for incident energies between 3.5 and 6.0 MeV simultaneously with the cross-section of the N14(α,α)N14 reaction at 165°. Interference between these two reactions at the angle of 165° and around 3.9 MeV was taken into account. The technique used is very powerful, thanks to the Ta450 nm/C target being implanted with a high dose of nitrogen. The N14(α,p0)O17 reaction exhibits some resonances allowing traces of nitrogen to be quantified. This reaction also offers an alternative to the N14(d,α)C12 and N14(H3e,p)O16 nuclear reactions for profiling nitrogen in the first few microns below the surface. Moreover, by using α-particles, Rutherford backscattering spectroscopy can be performed simultaneously with a good mass resolution to depth profile high Z elements in the sample. The sensitivity of these reactions (0.1%) has been tested by measuring the nitrogen traces in a titanium oxide film deposited on silicon. Depth profiling of nitrogen in a TiN layer on a silicon substrate was also performed. In addition, we publish for the first time some cross-sections values for the N14(α,p1)O17 reaction at 90° and 165°; this measurement is a challenging task.

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)0.001
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.039
GPT teacher head0.272
Teacher spread0.233 · 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

Citations29
Published2008
Admission routes1
Has abstractyes

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