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Record W2145685655 · doi:10.1109/ultsym.1991.234267

Characterization of texture in hexagonal materials using a line focus acoustic microscope

2002· article· en· W2145685655 on OpenAlexaff
P. J. Kielczynski, J. F. Bussière

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsFocus (optics)Hexagonal crystal systemTexture (cosmology)Characterization (materials science)Materials scienceMicroscopeLine (geometry)Acoustic microscopyMicroscopyOpticsArtificial intelligenceComputer scienceNanotechnologyImage (mathematics)GeometryPhysicsCrystallographyMathematicsChemistry

Abstract

fetched live from OpenAlex

A line focus acoustic microscope (LFAM) was used to measure the angular distribution of longitudinal surface skimming waves in Zr-2.5% wt. Nb samples exhibiting orthorhombic macroscopic symmetry. Using the information from longitudinal wave scans obtained on three principal planes, the authors attempt to determine as much information as possible about the five independent texture coefficients, W/sub lmn/, without any prior knowledge of the single-crystal elastic constants. In general, it is found that only ratios of the texture coefficients and the isotropic longitudinal velocity component can be determined from the ultrasonic measurements, when performed on hexagonal materials with orthorhombic macroscopic symmetry. The results are averaging method independent and do not require any information about the density of the material.>

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.204
Teacher spread0.189 · 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 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

Citations1
Published2002
Admission routes1
Has abstractyes

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