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THE SLICED BOMAB PHANTOM: A NEW VARIANT FOR INTERCOMPARISON

2006· article· en· W2009059913 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Physics · 2006
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsHealth Canada
Fundersnot available
KeywordsImaging phantomMonte Carlo methodUSableCalibrationWhole body countingComputer sciencePhysicsMedical physicsNuclear physicsOpticsMathematicsStatistics

Abstract

fetched live from OpenAlex

Previously, this laboratory conceptualized a new phantom for calibration or performance testing of whole body counters using Monte Carlo simulations. This paper describes the physical reality that was created from the Monte Carlo design project and compares its counting efficiency to that of a conventional BOMAB phantom using two whole body counters. In one counter (NaI based) the agreement between the two phantoms was +/-8% and in the second counter (Ge based) the agreement was +/-5% at all the energies measured (126 keV, 661 keV, 1172 keV, 1330 keV). The advantage of the sliced phantom is that the sources are solid, sealed, and cannot leak activity thereby simplifying packing for shipment if the phantom is classified as a Dangerous Good. The new phantom is, therefore, ideal for uses that involve shipment, such as an intercomparison exercise. The phantom is also re-usable as the sources can be changed.

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.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.917
Threshold uncertainty score0.219

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 head0.035
GPT teacher head0.363
Teacher spread0.327 · 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