MétaCan
Menu
Back to cohort

Mapping 3D doses in water with a cable robot equipped with plastic scintillator

2024· article· en· W4400785272 on OpenAlexaff
Louis Archambault, Ramin Mersi, Simon Foucault, Frédérik Berthiaume, Boby Lessard, François Therriault‐Proulx, Philippe Cardou

Bibliographic record

VenueJournal of Physics Conference Series · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsScintillatorRobotEnvironmental scienceComputer scienceRemote sensingGeologyArtificial intelligenceTelecommunicationsDetector

Abstract

fetched live from OpenAlex

Abstract This work presents the first use of a cable robot for 3D dosimetry. Its design was optimized to operate in water and offer five degrees of freedom. It was equipped with a plastic scintillation detector. The cables and the end effector were made of plastic, thus making all components inside the phantom water equivalent. Feasibility and reproducibility was demonstrated using a 6MV beam. The cable robot prototype had a usable workspace of 40 cm in each direction and could rotate over 90 degrees in both the polar and azimuthal directions. It was tested at speeds of up to 120.8 mm/s. Position precision was within 2.5 mm for translation and within 1.1 mm for rotations about a fixed point. This new robotic dosimetry system is more versatile and can address limitations of current water phantoms that are constrained to only 3 translation axes.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.248
Teacher spread0.235 · 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
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Physics Conference SeriesSame topicAdvanced Radiotherapy TechniquesFrench-language works237,207