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Record W2976683072 · doi:10.1002/mp.13782

Erratum: Monte Carlo study of ionization chamber magnetic field correction factors as a function of angle and beam quality. [Med. Phys. 45(2) p. 908‐925 (2018)]

2019· erratum· en· W2976683072 on OpenAlexaff
Victor Malkov, D. W. O. Rogers

Bibliographic record

VenueMedical Physics · 2019
Typeerratum
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsIonization chamberOrientation (vector space)Monte Carlo methodPhysicsIonizationBeam (structure)OpticsField sizeMaterials scienceIonStatisticsMathematicsGeometry

Abstract

fetched live from OpenAlex

Figures 6 and 8 in our 2018 paper1 were found to be incorrectly plotted and should have the data flipped about the 180 mark of the angle axis. The updated figures are provided below. This error impacts Table III of the paper and the values in the 90 and 270 columns must be exchanged to provide the corrected Table III below. ”This is observed for all chambers, and is particularly highlighted for the Co simulations of the Exradin A1SL, Exradin A12S, and the PTW 31006 in which the chamber dose, in comparison to the 0 T results, decreases near the C-II orientation and increases near the C-IV orientation." “This is observed for all chambers, and is particularly highlighted for the Co simulations of the Exradin A1SL, Exradin A12S, and the PTW 31006 in which the chamber dose, in comparison to the 0 T results, increases near the C-II orientation and decreases near the C-IV orientation." © 2019 American Association of Physicists in Medicine [https://doi.org/10.1002/mp.13782] The authors thank Arman Sarfehnia and Viktor Iakovenko for bringing this error to our attention through their careful experimental measurements of ion chamber response as a function of angle in a 1.5 T magnetic field2.

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)0.002
metaresearch head score (Gemma)0.024
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.005

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 head0.011
GPT teacher head0.281
Teacher spread0.270 · 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
GenreOther

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

Citations8
Published2019
Admission routes1
Has abstractyes

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