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Record W2461075557 · doi:10.1118/1.4955703

SU‐F‐E‐17: A Dedicated Teaching and Research Linac as a Stepping Stone to Introduce Medical Physics to Students

2016· article· en· W2461075557 on OpenAlexaff
Luc Beaulieu, L Gingras, Michael F. Bergeron, Louis Archambault

Bibliographic record

VenueMedical Physics · 2016
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsDawson CollegeCegep de ThetfordCegep de Sainte FoyCegep de Trois-RivieresUniversité Laval
Fundersnot available
KeywordsTruebeamLinear particle acceleratorSession (web analytics)Medical physicsMedical physicistPhysicsMedical imagingPhysics educationPresentation (obstetrics)Nuclear medicineComputer scienceMedicineOpticsRadiology

Abstract

fetched live from OpenAlex

Purpose: This work describes how a non‐clinical, research and teaching Linac is used as an extremely motivating and exciting way to introduce students to medical physics. Methods: The dedicated facility was inaugurated in 2014. The facility is composed of a fully equipped and functional state‐of‐the‐art Varian TrueBeam Linac and a complete set of physics instruments and QA phantoms for the Linac and onboard imaging. The Linac bunker and treatment console are oversized such that a class of 12–15 can comfortably fit, seated if needed for longer sessions. A 3cr undergraduate laboratory course that includes medical imaging, x‐ray source characterization (mAs, kVp, and filtering) and many others including an introductory Linac laboratory was created. The latter is composed of one general 4‐hours session and a weekly 4‐hours session for teams of two students. The general session includes a hands‐on presentation of the Linac, its environment and a formal safety and radiation protection course (with an exam). Results: Since the winter of 2015, senior undergraduate (total of 15) pursuing either the medical physics or the biomedical engineering tracks can register. At the Linac, the students are allowed full control of the experiments, including set‐up and irradiation. Supervisor intervention is limited to safety concerns for students or equipment. Measurements of output factors using two chambers (regular and small field) for various field sizes (1×1 to 30×30 cm2) and of detailed depth‐dose curves for 6 MV, 6 and 12 MeV beams are to be performed and discussed in a formal report. Conclusion: Full access to, and control of, a Linac is the high point of this course. It provides a glimpse of medical physics and generates an experimental background for those continuing to CAMPEP programs. This dedicated, non‐clinical facility further enable enhance CAMPEP graduate teaching and research activities not possible with a clinical device.

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)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.054
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0540.019

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 head0.037
GPT teacher head0.486
Teacher spread0.449 · 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 designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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