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Record W2728996425 · doi:10.3747/co.24.3484

Current Practice in Total-Body Irradiation: Results of a Canada-Wide Survey

2017· article· en· W2728996425 on OpenAlexafffundvenueabout
Ryan Studinski, D Fraser, Rajiv Samant, M MacPherson

Bibliographic record

VenueCurrent Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsOttawa Hospital
FundersOrganisation Canadienne des Physiciens Médicaux
KeywordsMedicineTotal body irradiationClinical PracticeData scienceFamily medicineSurgeryComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Total-body irradiation (tbi) is used to condition patients before bone marrow transplant. A variety of tbi treatment strategies have been described and implemented, but no consensus on best practice has been reached. We report on the results of a survey created to assess the current state of tbi delivery in Canada. RESULTS: A 19-question survey was distributed to 49 radiation oncology programs in Canada. Responses were received from 20 centres, including 12 centres that perform tbi. A variety of tbi dose prescriptions was reported, although 12 Gy in 6 fractions was used in 11 of the 12 centres performing tbi. Half of the centres also reported using a dose prescription unique to their facility. Most centres use an extended-distance parallel-opposed-pair technique, with the patient standing or lying on a stretcher against a wall. Others translate the patient under the beam, sweep the beam over the patient, or use a more complicated multi-field technique. All but 1 centre indicated that they attenuate the lung dose; only 3 centres indicated attenuating the dose for other organs at risk. The survey also highlighted the considerable resources used for tbi, including extra staff, prolonged planning and treatment times, and use of locally developed hardware or software. CONCLUSIONS: At transplant centres, tbi is commonly used, but there is no commonly accepted approach to planning and treatment delivery. The important discrepancies in practice between centres in Canada creates an opportunity to prompt more discussion and collaboration between centres, improving consistency and uniformity of practice.

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 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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
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 head0.097
GPT teacher head0.420
Teacher spread0.322 · 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 teacher head, 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

Citations34
Published2017
Admission routes4
Has abstractyes

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