MétaCan
Menu
Back to cohort
Record W4404590196 · doi:10.1079/cabireviews.2024.0054

Tortuosity transformation of near-infrared diffuse reflectance spectra for the detection of enhanced and aggregate spectral changes with reference to dietary preferences of elephants

2024· article· en· W4404590196 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.

Bibliographic record

VenueCABI Reviews · 2024
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Chemometric Analyses
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsTortuosityDiffuse reflectionReflectivityAggregate (composite)Diffuse reflectance infrared fourier transformRemote sensingEnvironmental scienceMaterials scienceSpectral lineBiological systemOpticsGeographyChemistryPorosityPhysicsNanotechnologyBiologyComposite material

Abstract

fetched live from OpenAlex

Abstract Tortuosity, as a transformation of near-infrared spectra, is illustrated in this communication. To overcome the loss of any grouping structure, due to substrate-sample treatment or different particle size effects, a new autoregression scatter correction is described that preserves such stratification. Tortuosity applications are well established in medical, engineering and diffusion studies. Herein, tortuosity application to near-infrared diffuse reflectance spectra is presented as an additional tool for spectral change investigations.

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 score0.056
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.049
GPT teacher head0.313
Teacher spread0.264 · 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