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Record W2093015174 · doi:10.1080/0267829031000089933

Simulation of texture formation processes in carbonaceous mesophase fibres

2003· article· en· W2093015174 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLiquid Crystals · 2003
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsMcGill University
Fundersnot available
KeywordsMesophaseMaterials scienceTexture (cosmology)PlanarMesoscopic physicsPolarComposite materialLiquid crystalMicrostructureMelt spinningTopological defectChemical physicsChemical engineeringSpinningCondensed matter physicsOptoelectronicsComputer science

Abstract

fetched live from OpenAlex

Abstract Carbon fibres are spun from carbonaceous mesophases using standard melt spinning techniques. These melt spun carbon fibres exhibit a set of distinct cross-sectional textures. Two widely reported textures in literature are the planar radial (PR) and planar polar (PP). This work uses a mesoscopic model, based on the classical Landau-de Gennes theory of liquid crystals adapted to carbonaceous mesophases, to elucidate the principles that control the texture formation processes. The model is able to capture the microstructure and the formation of the PR and PP textures. A phase diagram for classical PR and PP textures has been constructed in terms of temperature and fibre radius, thus establishing the processing conditions and geometric factors that lead to the selection of these textures. The multipath formation process of the planar polar texture through defect splitting, direct planar polar formation, and defect annihilation has been thoroughly characterized. The results of this work provide new knowledge for optimization and control of mesophase carbon fibre textures.

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.

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)0.002
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 score0.082
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.022
GPT teacher head0.310
Teacher spread0.289 · 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