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Record W4401856241 · doi:10.3390/gels10080540

Fabrication and Characterization of Brain Tissue Phantoms Using Agarose Gels for Ultraviolet Vision Systems

2024· article· en· W4401856241 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGels · 2024
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsABB (Canada)
FundersConsejo Nacional de Ciencia y TecnologíaCanadian Institute for Theoretical Astrophysics
KeywordsImaging phantomBrain tissueBiomedical engineeringMaterials scienceBiological tissueCharacterization (materials science)UltravioletLight scatteringComputer scienceAgaroseOpticsScatteringNanotechnologyOptoelectronicsPhysicsChemistryMedicine

Abstract

fetched live from OpenAlex

Recreating cerebral tissue using a tissue-mimicking phantom is valuable because it provides a tool for studying physiological and biological processes related to tissues without the necessity of performing the study directly in the tissue or even in a patient. The reproduction of the optical properties allows investigation in areas such as imaging, optics, and ultrasound, among others. This paper presents a methodology for manufacturing agarose-based phantoms that mimic the optical characteristics of brain tissue using scattering and absorbing agents and proposes combinations of these agents to recreate the healthy brain tissue optical coefficients within the wavelength range of 350 to 500 nm. The results of the characterization of the manufactured phantoms propose ideal combinations of the used materials for their use in controlled environment experiments in the UV range, following a cost-effective methodology.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.258

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 head0.018
GPT teacher head0.372
Teacher spread0.354 · 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