MétaCan
Menu
Back to cohort

Advances in Cholesteric Liquid Crystals

2020· book· en· W4245538605 on OpenAlexfundno aff
Michel Mitov

Bibliographic record

Venuenot available
Typebook
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesRussian Science FoundationJinan UniversityNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsCholesteric liquid crystalLiquid crystalReflection (computer programming)Materials scienceNanotechnologySmart materialOpticsOptoelectronicsComputer sciencePhysics

Abstract

fetched live from OpenAlex

With their helical structure, cholesteric liquid crystals figure prominently in liquid crystal science. The selective reflection of light is their flagship property, and they offer a myriad of applications as advanced optical materials with multiscale properties. The cholesteric structure is also a ubiquitous design in the animal and plant kingdoms. This book contains eight contributions on fundamental investigations about defects, textures and structures of cholesteric materials, and experimental studies aimed at applications such as temperature sensors, head-up displays for improving automobile driving safety, or smart windows.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0440.041

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 head0.024
GPT teacher head0.308
Teacher spread0.284 · 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 designNot applicable
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

Citations7
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicLiquid Crystal Research AdvancementsFrench-language works237,207