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Record W2000635130 · doi:10.1002/mats.200900023

Mathematical Modeling of PAG‐ and NIPAM‐Based Polymer Gel Dosimeters Contaminated by Oxygen and Inhibitor

2009· article· en· W2000635130 on OpenAlex
V I Koeva, Shahab Daneshvar, Robert J. Senden, A. H. M. Imam, L J Schreiner, Kimberley B. McAuley

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMacromolecular Theory and Simulations · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsCancer Care South EastQueen's University
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaMitacsQueen's University
KeywordsDosimeterContaminationOxygenCopolymerAcrylamidePolymerLimiting oxygen concentrationPolymerizationAbsorbed doseMaterials scienceChemistryRadiationRadiochemistryBiological systemChemical engineeringPhysicsOrganic chemistryNuclear physicsEngineering

Abstract

fetched live from OpenAlex

Abstract A mathematical model for crosslinking copolymerization of acrylamide (or NIPAM) and N,N ' ‐ methylenebisacrylamide is extended to account for contamination by oxygen and the inhibitor MEHQ. This model improves basic understanding of interactions among oxygen, MEHQ and polymerization reactions in gel dosimeters that are used to verify radiation doses delivered by cancer treatment equipment. Improved parameter estimates result in a good match between model predictions and data. The model predicts that a larger absorbed dose will be required to overcome the oxygen inhibition with increasing oxygen contamination, in agreement with experimental data. The model also predicts that MEHQ, in the absence of oxygen, has almost no influence on dosimeter response. magnified image

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

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

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 head0.005
GPT teacher head0.250
Teacher spread0.245 · 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