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Record W2753920448 · doi:10.3329/bjmp.v8i1.33930

Responses of LiF Thermoluminescence Dosimeters to Diagnostic 60Co Teletherapy Beams

2017· article· en· W2753920448 on OpenAlexaff
M Obaidur Rahman, Md. Ashraful Hoque, Md Shakilur Rahman, A. Nishara Begum

Bibliographic record

VenueBangladesh Journal of Medical Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsThermoluminescent dosimeterDosimeterThermoluminescenceImaging phantomNuclear medicineIrradiationDosimetryIonizing radiationMedical physicsAbsorbed doseMedicinePhysicsMaterials scienceNuclear physics

Abstract

fetched live from OpenAlex

Thermoluminescence Dosimeter (TLD) is used as an ionizing radiation detector in the field of clinical radiotherapy, diagnostic radiology, personal radiation monitoring as well as in environmental radiation dosimetry. The sensitivity of all the TLDs is not the same even though the manufacturer produced them in the same batch. The response of TLD at various doses is also not always linear. In the present study fifty-seven rod shaped LiF TLDs had been irradiated by doses of 50cGy, 100cGy, 150cGy and 200cGy using 60Co teletherapy unit of Dhaka Medical College (Alcyon II, CGR, McV, France). The TLDs were placed in the grooves of a slab phantom and then covered by a 0.5cm thick plexiglass sheet. The phantom was then irradiated in the reference condition (10x10cm2 field size, 80cm SSD). After irradiation, readout of TLDs was done using a Harshaw TLD reader (Model 3500). Measurements were performed three times for each dose value and their average was taken. For convenience all fifty-seven TLDs were divided into nineteen groups. Grouping was done according to the response of the TLDs for a fixed dose value. In a particular group of TLDs, variation of the response of the dosimeters is the smallest one. The dose (cGy) – response (nC) linearity curve of TLDs for each of the nineteen groups showed to be very close to unity.Bangladesh Journal of Medical Physics Vol.8 No.1 2015 14-21

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.018
GPT teacher head0.326
Teacher spread0.309 · 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 designOther design
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

Citations3
Published2017
Admission routes1
Has abstractyes

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