MétaCan
Menu
Back to cohort
Record W2311271662 · doi:10.1016/j.dib.2016.03.052

Energetic and kinetic dataset on interaction of the vacancy and self-interstitial atom with the grain boundary in α-iron

2016· article· en· W2311271662 on OpenAlex
Xiangyan Li, Wei Liu, Yichun Xu, C.S. Liu, Bicai Pan, Yunfeng Liang, Q.F. Fang, Junling Chen, Guang–Nan Luo, Guang-Hong Lü, Zhiguang Wang

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueData in Brief · 2016
Typearticle
Languageen
FieldMaterials Science
TopicFusion materials and technologies
Canadian institutionsnot available
FundersHefei Science Center, Chinese Academy of SciencesHefei Institutes of Physical Science, Chinese Academy of SciencesAlzheimer Society of B.C.International Atomic Energy AgencyChinese Academy of SciencesCenter for Computational Sciences, University of KentuckyNational Magnetic Confinement Fusion Program of ChinaNational Natural Science Foundation of China
KeywordsVacancy defectAnnihilationGrain boundaryKinetic energyAtom (system on chip)DiffusionMaterials scienceBoundary (topology)Condensed matter physicsSelf-diffusionAtomic physicsPhysicsMetallurgyNuclear physicsThermodynamicsMicrostructure

Abstract

fetched live from OpenAlex

We provide the dataset of the vacancy (interstitial) formation energy, segregation energy, diffusion barrier, vacancy-interstitial annihilation barrier near the grain boundary (GB) in bcc-iron and also the corresponding interactive range. The vacancy-interstitial annihilation mechanisms in the bulk, near the GB and at the GB at across scales were given.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.710
Threshold uncertainty score0.133

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 communication0.0000.000
Open science0.0000.001
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 head0.013
GPT teacher head0.246
Teacher spread0.232 · 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