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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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.003

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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

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