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On the Processes Leading to Carotenemia-Elicited Changes in the Spectral Responses and Chromatic Attributes of Human Skin

2024· article· en· W4405488682 on OpenAlexaff
Gladimir V. G. Baranoski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicColor Science and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsChromatic scaleComputer sciencePhysicsOptics

Abstract

fetched live from OpenAlex

The presence of large concentrations of carotenoids within human skin, normally referred to as carotenemia, has been associated with a myriad of photobiological phenomena with a direct impact on the population's health. Despite the diverse body of biomedical research in this area, there are still key aspects that remain elusive with respect to the cutaneous accumulation of these compounds and their effects on skin and light interactions. Accordingly, the current understanding about the spectral responses and chromatic attributes of affected skin specimens, notably those characterized by high levels of pigmentation, is hindered by empirical information paucity. In this paper, we address these interconnected processes and their implications for the assessment of individuals' carotenemic status. To achieve that, we conducted controlled in silico experiments supported by measured data. We also discuss different strategies for the cost-effective monitoring of carotenoids' accumulation in skin sites more exposed to ultraviolet light and characterized by distinct levels of pigmentation.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.031
GPT teacher head0.312
Teacher spread0.281 · 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 designObservational
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

Citations2
Published2024
Admission routes1
Has abstractyes

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