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Record W3049376848 · doi:10.1139/cjp-2020-0286

Pocket formula for incoherent scattering cross section

2020· article· en· W3049376848 on OpenAlexvenueno aff
H.C. Manjunatha, L. Seenappa, K.N. Sridhar

Bibliographic record

VenueCanadian Journal of Physics · 2020
Typearticle
Languageen
FieldMaterials Science
TopicRadiation Shielding Materials Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsIncoherent scatterCross section (physics)ScatteringRange (aeronautics)Atomic numberAtomic physicsScattering lengthNuclear cross sectionEnergy (signal processing)Scattering cross-sectionNuclear physicsSimple (philosophy)Computational physicsElastic scatteringOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

We have achieved a simple empirical formula for incoherent scattering cross section based on the data available in the literature. The present formula produces incoherent scattering cross section values of all atoms for the atomic number range 1 < Z < 100 in the energy range 1 keV < E < 100 GeV with the simple inputs of atomic number (Z) and energy (E) in keV. The percentage of deviation of incoherent scattering cross section of the present formula is less than ±3%. The values produced by the present formula agree well with the experiments. The present formula is useful in the fields of radiation physics and nuclear physics.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.033
GPT teacher head0.269
Teacher spread0.236 · 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 designTheoretical or conceptual
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

Citations1
Published2020
Admission routes1
Has abstractyes

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