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Record W1985493150 · doi:10.1088/0031-9155/53/13/n01

Deformable and durable phantoms with controlled density of scatterers

2008· article· en· W1985493150 on OpenAlexaff
Charles-Étienne Bisaillon, Guy Lamouche, Romain Maciejko, M. Dufour, Jean‐Pierre Monchalin

Bibliographic record

VenuePhysics in Medicine and Biology · 2008
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsPolytechnique MontréalNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceImaging phantomOptical coherence tomographySpeckle patternOpticsBiomedical engineeringSiliconeFabricationComposite materialPhysicsMedicine

Abstract

fetched live from OpenAlex

We have developed deformable and durable optical tissue phantoms with a simple and well-defined microstructure including a novel combination of scatterers and a matrix material. These were developed for speckle and elastography investigations in optical coherence tomography, but should prove useful in many other fields. We present in detail the fabrication process which involves embedding silica microspheres in a silicone matrix. We also characterize the resulting phantoms with scanning electron microscopy and optical measurements. To our knowledge, no such phantoms were proposed in the literature before. Our technique has a wide range of applicability and could also be adapted to fabricate phantoms with various optical and mechanical properties.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.090
GPT teacher head0.301
Teacher spread0.211 · 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

Citations37
Published2008
Admission routes1
Has abstractyes

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