MétaCan
Menu
Back to cohort
Record W2045564518 · doi:10.1364/ao.49.006324

Measurement of the optical properties of a two-layer model of the human head using broadband near-infrared spectroscopy

2010· article· en· W2045564518 on OpenAlexaff
Olivia Pucci, Vladislav Toronov, Keith St. Lawrence

Bibliographic record

VenueApplied Optics · 2010
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsLawson Health Research InstituteToronto Metropolitan University
Fundersnot available
KeywordsOpticsMaterials scienceSpectroscopyAbsorption (acoustics)BroadbandAttenuation coefficientInfraredScatteringNear-infrared spectroscopyLayer (electronics)DetectorAbsorption spectroscopyChromophoreSpectral linePhysics

Abstract

fetched live from OpenAlex

We present the development of a continuous-wave method of quantifying the optical properties of a two-layered model of the human head using a broadband spectral approach. Absolute absorption and scattering properties of the upper and lower layers of phantoms with known optical properties were reconstructed from steady-state multi-distance measurements by performing differential fit analysis of the near-infrared reflectance spectrum between 700 and 1000 nm. From spectra acquired at 10, 20, and 30 mm, the concentration of a chromophore in the bottom layer was determined within an error of 10% in the presence of a 15 mm thick top layer. These results demonstrate that our method was able to determine the optical properties of the lower layer, which represents brain, with acceptable error at specific source-detector distances.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.058
GPT teacher head0.319
Teacher spread0.260 · 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

Citations49
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueApplied OpticsSame topicOptical Imaging and Spectroscopy TechniquesFrench-language works237,207