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Record W2106268782 · doi:10.6000/1927-5129.2013.09.25

Radiation Exposure to Nuclear Medicine Technologists During Different Diagnostic Techniques

2013· article· en· W2106268782 on OpenAlexvenueno aff
Sumera Perveen, Arfa Mubashir, Humera Noreen

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2013
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear medicineMedicineRadiation exposureDosimeterThalliumRadiation doseNuclear radiationMedical physicsRadiologyDosimetryRadiochemistryMaterials scienceChemistry

Abstract

fetched live from OpenAlex

Nuclear Medicine is being widely used, now a days, for different diagnostic purposes. The present study was planned to find out the radiation exposure to nuclear medicine technologists from radioactive patients who have gone through different diagnostic techniques. This study was carried out at Punjab Institute of Nuclear Medicine (PINUM), Faisalabad (Pakistan). In order to carry out this activity, data was collected from the nuclear medicine diagnostic techniques i.e., heart scans (Rest and Stress MIBI), bone scans, renal scans, liver scans, thyroid scans and Thallium heart scans. The radiation exposure was recorded using pen dosimeter (Arrow-Tech W138) having range 0-200mR. Heart scan (Stress MIBI) was taken as standard as it showed maximum exposure (0.584 mR) and equivalent dose corresponding to this exposure (5.85μSv) amongst all scans.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.012
GPT teacher head0.262
Teacher spread0.251 · 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 designBench or experimental
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
Published2013
Admission routes1
Has abstractyes

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