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Record W2508153511 · doi:10.1118/1.4961838

Sci‐Fri AM: Quality, Safety, and Professional Issues 02: Recent work on TQC Suite and Data from a National survey on Community Uptake

2016· article· en· W2508153511 on OpenAlexaffabout
Kyle Malkoske, Michelle Nielsen, Erika Brown, Kevin R. Diamond, Normand Frenière, John A. Grant, Natalie Pomerleau‐Dalcourt, Jason Schella, L J Schreiner, L. Tantot, Eduardo Villareal Barajas, David Sasaki, Marie‐Pierre Milette, Marie‐Joëlle Bertrand, Jean‐Pierre Bissonnette

Bibliographic record

VenueMedical Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-QuébecCancerCare ManitobaHealth Sciences CentreJuravinski Cancer CentreTrillium Health CentreBC Cancer Agency
Fundersnot available
KeywordsSuiteQuality (philosophy)Quality assuranceWork (physics)Process (computing)Engineering managementUsabilityControl (management)General partnershipWorkflowComputer sciencePlan (archaeology)EngineeringProcess managementOperations managementBusinessDatabasePolitical scienceGeography

Abstract

fetched live from OpenAlex

The Canadian Partnership for Quality Radiotherapy (CPQR) and the Canadian Organization of Medical Physicist's (COMP) Quality Assurance and Radiation Safety Advisory Committee (QARSAC) have worked together in the development of a suite of Technical Quality Control (TQC) Guidelines for radiation treatment equipment and technologies, that outline specific performance objectives and criteria that equipment should meet in order to assure an acceptable level of radiation treatment quality. Early community engagement and uptake survey data showed 70% of Canadian centers are part of this process and that the data in the guideline documents reflect, and are influencing the way Canadian radiation treatment centres run their technical quality control programs. As the TQC development framework matured as a cross‐country initiative, guidance documents have been developed in many clinical technologies. Recently, there have been new TQC documents initiated for Gamma Knife and Cyberknife technologies where the entire communities within Canada are involved in the review process. At the same time, QARSAC reviewed the suite as a whole for the first time and it was found that some tests and tolerances overlapped across multiple documents as single tests could pertain to multiple quality control areas. The work to streamline the entire suite has allowed for improved usability of the suite while keeping the integrity of single quality control areas. The suite will be published by the JACMP, in the coming year.

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)0.022
metaresearch head score (Gemma)0.087
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.641
Threshold uncertainty score0.723

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.087
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0070.016
Science and technology studies0.0040.003
Scholarly communication0.0040.004
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0210.005

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 head0.118
GPT teacher head0.427
Teacher spread0.309 · 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 designObservational
Domainnot available
GenreEmpirical

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 routes2
Has abstractyes

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