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Record W102771789

Radiation doses to patients receiving computed tomography examinations in British Columbia.

2006· article· en· W102771789 on OpenAlexaffabout
John E. Aldrich, Ana-Maria Bilawich, John R Mayo

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicinePelvisAbdomenNuclear medicineComputed tomographyEffective dose (radiation)RadiologyRadiation doseRadiation exposure
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To estimate the diagnostic reference levels and effective radiation dose to patients from routine computed tomography (CT) examinations in the province of British Columbia, Canada. METHODS: The patient weight, height and computed tomography dose index or dose linear product (DLP) were recorded on study sheets for 1070 patients who were referred for clinically indicated routine CT examinations at 18 radiology departments in British Columbia. Sixteen of the scanners were multidetector row scanners. RESULTS: The average patient dose varied from hospital to hospital. The largest range was found for CT of the abdomen, for which the dose varied from 3.6 to 26.5 (average 10.1) mSv. For head CT, the range was 1.7 to 4.9 (average 2.8) mSv; for chest CT, it was 3.8 to 26 (average 9.3) mSv; for pelvis CT, it was 3.5 to 15.5 (average 9.0) mSv; and for abdomen-pelvis CT, it was 7.3 to 31.5 (average 16.3) mSv. Reference dose values were calculated for each exam. These DLP values are as follows: head, 1300 mGy cm; chest, 600 mGy cm; abdomen, 920 mGy cm; pelvis, 650 mGy cm; and abdomen-pelvis, 1100 mGy cm. CONCLUSION: Among hospitals, there was considerable variation in the DLP and patient radiation dose for a specific exam. Reference doses and patient doses were higher than those found in similar recent surveys carried out in the United Kingdom and the European Union. Patient doses were similar to those found in a recent survey in Germany.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.201
Teacher spread0.193 · 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

Citations76
Published2006
Admission routes2
Has abstractyes

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