MétaCan
Menu
Back to cohort
Record W2291847566 · doi:10.14288/1.0104934

Plastic deformation of lithium fluoride.

2011· article· en· W2291847566 on OpenAlexaff
K. N. Street

Bibliographic record

VenuecIRcle (University of British Columbia) · 2011
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Properties and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDeformation (meteorology)Lithium (medication)FluorideLithium fluorideForensic engineeringMaterials scienceGeologyComposite materialChemistryPsychologyEngineering

Abstract

fetched live from OpenAlex

A nonuniform annealing rate of color centers in LiF is attributed to a nonuniform density of dislocations which, in turn, is a direct consequence of the cleaving process. The tensile deformation properties of annealed LiF crystals were determined over the temperature range – 196 ⁰C. to +60 ⁰C. Several tests were also carried out on ɣ - irradiated specimens at ambient temperatures. A transition occurs in the work hardening rate during stage II deformation. Experiments involving both strain-rate and temperature cycling were performed over the limited temperature range of - 60 to +60 ⁰C. The results were analyzed in terms of rate theory expressions and indicated that the rate controlling mechanism for dislocation motion in stage IIA is probably the nonconservative motion of jogs in screw dislocations. Stage IIB hardening is more likely controlled by dislocation intersections. Evidence is presented which indicated that stress relaxation experiments may provide an extremely easy technique for the determination of the internal flow stress. Values obtained from such experiments on LiF agree remarkably well with those obtained from rate theory experiments.

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 score0.004
Threshold uncertainty score0.012

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)0.0040.000

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 head0.015
GPT teacher head0.164
Teacher spread0.149 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venuecIRcle (University of British Columbia)Same topicMaterial Properties and ApplicationsFrench-language works237,207