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Anisotropic Fluid Phase Formed by Ionic Liquid-Crystalline Materials with Ammonium Ions

2017· article· en· W2592799352 on OpenAlexvenueno aff
Shiori Tomitaka, Jinzhi Wu, Masanori Nata, Seiji Ujiie

Bibliographic record

VenueJournal of Applied Solution Chemistry and Modeling · 2017
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsnot available
Fundersnot available
KeywordsDifferential scanning calorimetryPhase (matter)IonAnisotropyMaterials scienceTexture (cosmology)DiffractionCrystallographyIonic bondingPerpendicularLiquid crystalOpticsAnalytical Chemistry (journal)ChemistryGeometryChromatographyOrganic chemistryPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Ionic liquid-crystalline materials (ILCMs) with ammonium ions were synthesized. Their thermal and orientational properties were studied by polarizing microscopy, differential scanning calorimetry, and X-ray diffraction (XRD). The ILCMs formed the smectic A phase on heating and cooling. A focal conic fan texture was observed in the phase. In addition, the ILCMs spontaneously formed a perpendicular alignment in the smectic A phase. The XRD patterns of the ILCMs consisted of sharp reflections in the small-angle region and broad band in the wide-angle region in the smectic A phase.

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)0.001
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 score0.092
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.313
Teacher spread0.285 · 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 teacher head, 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

Citations0
Published2017
Admission routes1
Has abstractyes

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