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Record W2747493634 · doi:10.17488/rmib.38.1.32

Analysis of the absorption spectra of EBT2 and EBT3 radiochromic films

2017· article· en· W2747493634 on OpenAlexaff
Elsa Yazmín León-Marroquín, M.A. Camacho-López, Olivia Amanda García‐Garduño, Juan A. Herrera-González, J. Eduardo Villarreal‐Barajas, C. A. Martínez-Quiroz, D. De la Cruz-Pérez, Gerardo Jiménez-Aviles

Bibliographic record

VenueRevista Mexicana de Ingeniería Biomédica · 2017
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAbsorption spectroscopyAbsorption (acoustics)Spectral lineIrradiationMaterials scienceOpticsAnalytical Chemistry (journal)PhysicsChemistryNuclear physics

Abstract

fetched live from OpenAlex

To analyze the net absorption spectra of EBT2 and EBT3 radiochromic films to describe their influenceon the behavior of dose-response curves. The films were irradiated in a linear accelerator of 6 MV. The net absorption spectra were obtained with a UV / VIS spectrophotometer. Dose-response curves were obtained with a scanner, a He-Ne laser and a spectrophotometer. The absorption spectrum of the EBT2 shows three focused absorption bands that retain position and increase their intensity as a function of dose, however, this behavior is not observed in EBT3 films. The dose-response curve shows maximum sensitivity using the spectrophotometer, but does not show a defined behavior. Generation of new knowledge for the creation of new optical systems capable of amplifying the responsiveness of the films. Show the correlation between net absorption spectra and their influence on dose-response curves in three different optical systems. The behavior of absorption spectra combined with the behavior of the dose-response curves helps to discard the use of optical systems that do not guarantee a reliable clinical use.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.319
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueRevista Mexicana de Ingeniería BiomédicaSame topicPhotodynamic Therapy Research StudiesFrench-language works237,207