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BOMAB phantom variability: do small dimensional changes matter?

2008· article· en· W1985161741 on OpenAlexaff
Gary H. Kramer, Barry M. Hauck, Shannon Dang, Kevin Capello

Bibliographic record

VenueHealth Physics · 2008
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsHealth Canada
Fundersnot available
KeywordsImaging phantomMonte Carlo methodDetectorPhysicsCharacterization (materials science)Materials scienceOpticsBiomedical engineeringNuclear medicineMathematicsStatisticsMedicine

Abstract

fetched live from OpenAlex

The Human Monitoring Laboratory (HML) has had a number of BOMAB phantoms built over the years. Upon characterization, it has been found that the dimensions of the phantoms are always slightly different. This study has looked at the effect of these small variances in dimensions of the phantoms and compared the results to what is required in the industry standard using Monte Carlo simulations for three counting geometries: the HML's scanning detector whole body counter, the StandFast whole body counter, and the W-chair whole body counter. It has been found that the effect of these small variations on the performance of these phantoms is very minor (<5%). It is reassuring to find that small variations in manufacturing, even if individual sections are non-compliant, have such a minor effect on performance as to be considered a negligible effect for any counting system's geometry.

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 score0.375
Threshold uncertainty score0.403

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 head0.050
GPT teacher head0.311
Teacher spread0.261 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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