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Record W2004344258 · doi:10.1118/1.1388895

Investigation into the physical characteristics of active matrix flat panel imagers for radiotherapy

2001· article· en· W2004344258 on OpenAlexafffund
M. Lachaı̂ne, E Fourkal, B. G. Fallone

Bibliographic record

VenueMedical Physics · 2001
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsMcGill UniversityUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDetective quantum efficiencyOpticsMonte Carlo methodMaterials scienceCascadeImage qualityRadiationMatrix (chemical analysis)Active matrixFlat panel detectorLayer (electronics)DetectorPhysicsImage (mathematics)MathematicsComputer scienceChemistry

Abstract

fetched live from OpenAlex

The effect of physical characteristics on active matrix flat panel imagers (AMFPIs) at megavoltage energies is studied. The detective quantum efficiency (DQE) of both direct and indirect AMFPIs is modeled using a modified cascade analysis combined with Monte Carlo simulations. It is found that for a given thickness of the sensitive layer less than about 1 mm, there should be no significant difference between the detection techniques, but for larger mass thicknesses (> or = 1 mm) there should be an advantage to using direct detection if such thick layers can be manufactured. The effect of the front plate on both direct and indirect techniques is also explored in terms of both the DQE and scatter rejection. It is found that for small sensitive layer thicknesses (< or =0.3 mm) a front plate thickness of about 1 mm Cu is optimal, whereas for larger mass thicknesses about 0.4 mm Cu should lead to better image quality.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.328

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 head0.024
GPT teacher head0.312
Teacher spread0.288 · 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

Citations8
Published2001
Admission routes2
Has abstractyes

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