MétaCan
Menu
Back to cohort
Record W4402966724 · doi:10.35784/iapgos.6141

POLARIZATION-CORRELATION MAPPING OF MICROSCOPIC IMAGES OF BIOLOGICAL TISSUES OF DIFFERENT MORPHOLOGICAL STRUCTURE

2024· article· en· W4402966724 on OpenAlexaff
N. M. Kozan, Oleksandr Saleha, Olexander V. Dubolazov, Yuriy Ushenko, Iryna Soltys, O. G. Ushenko, O. V. Olar, V. G. Paliy, Saule Smailova

Bibliographic record

VenueInformatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska · 2024
Typearticle
Languageen
FieldEngineering
TopicOptical Polarization and Ellipsometry
Canadian institutionsMemorial University of Newfoundland
FundersNational Research FoundationNational Research Foundation of Ukraine
KeywordsPolarization (electrochemistry)CorrelationGeometryChemistryMathematics

Abstract

fetched live from OpenAlex

The results of polarization-correlation mapping of the fourth parameter of the two-point Stokes vector of microscopic images of histological sections of biological tissues with different architectonics of the optically anisotropic polycrystalline component are presented. The coordinate distributions of randomly generated values representing the modulus of the fourth parameter of the polarization-correlation vector from microscopic images of histological sections of fibrillar tissues (such as skin dermis) and parenchymal tissues (like spleen) have been replicated. The statistical analysis results of algorithmically generated coordinate distributions of random values representing the modulus of the fourth parameter of the polarization-correlation vector from microscopic images of histological sections of biological tissues with varying morphological structures are provided.

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)0.003
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInformatyka Automatyka Pomiary w Gospodarce i Ochronie ŚrodowiskaSame topicOptical Polarization and EllipsometryFrench-language works237,207