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Record W1978377658 · doi:10.1117/1.2400702

Time-resolved imaging of optical coefficients through murine chest cavities

2006· article· en· W1978377658 on OpenAlexfundno aff
Mark Niedre, Gordon M. Turner, Vasilis Ntziachristos

Bibliographic record

VenueJournal of Biomedical Optics · 2006
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsnot available
FundersNational Institute of Biomedical Imaging and BioengineeringNational Cancer InstituteNational Institutes of HealthTerry Fox Foundation
KeywordsOpticsDiffuse optical imagingOptical imagingTransmission (telecommunications)Photon countingAttenuation coefficientMaterials sciencePhoton diffusionLaserPreclinical imagingOptical phenomenaPhotonDiffusionPhysicsIn vivoTomographyComputer scienceLight source

Abstract

fetched live from OpenAlex

As small animal optical imaging and tomography are gaining popularity for interrogating functional and molecular events in vivo, it becomes increasingly necessary to gain knowledge of the optical properties of the species investigated to better understand and describe photon propagation through their tissues. To achieve characterization of the spatial variation of average optical properties through murine chest cavities, time- and spatially resolved measurements of femto-second laser pulse transmission are performed through mice using a high-speed gated image intensifier. Application of time-resolved diffusion theory for finite slab geometry is first confirmed on phantoms and then applied to in vivo measurements for spatially resolving and quantifying mouse optical properties. Photon transmission images through mouse chest cavities are further obtained at different time gates to visualize the spatial variation observed and confirm the optical coefficient patterns calculated.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.010
GPT teacher head0.295
Teacher spread0.285 · 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

Citations48
Published2006
Admission routes1
Has abstractyes

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