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Characterization of Fibres and Fibre Collectives with Common Laser Diffractometers

2000· article· en· W1982971277 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

VenueParticle & Particle Systems Characterization · 2000
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsNickel Institute
Fundersnot available
KeywordsDiffractionMaterials scienceOpticsCharacterization (materials science)LaserOrientation (vector space)Suspension (topology)Composite materialNanotechnologyPhysicsGeometryMathematics

Abstract

fetched live from OpenAlex

The method described utilises the effect that in many commercially available laser diffractometers a laminary flow of the suspension medium in the measurement cell exists. However, data analysis carried out using commercially available laser diffractometers is normally based upon the assumption that there is a statistical orientation of the particles in the measurement volume. The resulting diffraction patterns are, therefore, assumed to be centrosymmetric and ring-shaped. As a consequence, the detectors commonly used only record parts of the diffraction patterns. Based upon these assumptions, it is accepted that grain size analysis of fibrous particles gives an equivalent diameter between length and diameter. First experiments carried out using a Malvern Mastersizer X showed that fibres align in the flow direction. Analysis of the entire diffraction pattern should, therefore, provide information about the length and diameter of the fibres.

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)0.000
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 score0.263
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.188
Teacher spread0.179 · 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