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Record W2014708007 · doi:10.1088/0031-9155/51/8/n03

RadSim: a program to simulate individual particle interactions for educational purposes

2006· article· en· W2014708007 on OpenAlexaff
Frank Verhaegen, S Palefsky, F DeBlois

Bibliographic record

VenuePhysics in Medicine and Biology · 2006
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsMcGill UniversityMontreal General Hospital
Fundersnot available
KeywordsKinematicsPhotonMonte Carlo methodMode (computer interface)Computer scienceAtom (system on chip)ElectronPhysicsStatistical physicsChannel (broadcasting)Particle (ecology)SimulationComputational physicsClassical mechanicsNuclear physicsMathematicsOpticsStatisticsHuman–computer interaction

Abstract

fetched live from OpenAlex

A program was developed, RadSim, which can be used to simulate certain individual interactions of photons, electrons, positrons and alpha particles with a single atom for educational purposes. The program can be run in two modes: manual and simulated. In the manual mode, an individual particle undergoing a specified interaction with a target atom can be simulated, which essentially comes down to a graphical evaluation of kinematic equations. In the simulated mode, a preset number of identical particles are allowed to undergo a specified interaction type with a target atom. The exit channel of the interaction is sampled from probability distributions using Monte Carlo methods. The incoming and outgoing particles are visualized and the frequency distribution of the kinematic variables of the exit channel is displayed graphically. It has to be emphasized that RadSim was mainly developed for educational purposes.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.005

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 head0.223
GPT teacher head0.481
Teacher spread0.258 · 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 designSimulation or modeling
Domainnot available
GenreSoftware

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

Citations4
Published2006
Admission routes1
Has abstractyes

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