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Record W4233344845 · doi:10.22215/etd/2014-10198

New Zirconium Hydrogen Second Nearest Neighbor Modified Embedded Atom Method (MEAM) Potential For Simulation of Stacking Fault Energy Along the <0110> Path Of The Hexagonal Closely Packed Lattice Basal Plane

2014· dissertation· en· W4233344845 on OpenAlexaff
Nenad Vuksic

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsCarleton University
Fundersnot available
KeywordsZirconiumStackingHexagonal crystal systemk-nearest neighbors algorithmClose-packing of equal spheresStacking faultMaterials scienceLattice (music)CrystallographyBasal planeHexagonal latticeFault planeAtom (system on chip)HydrogenMolecular physicsCondensed matter physicsChemistryFault (geology)PhysicsMetallurgyComputer scienceParallel computingGeology

Abstract

fetched live from OpenAlex

New Zirconium Hydrogen Second Nearest Neighbor Modified Embedded Atom Method (MEAM) Potential For Simulation of Stacking Fault Energy Along the <0110> Path Of The Hexagonal Closely Packed Lattice Basal Plane

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.265
Teacher spread0.247 · 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 designSimulation or modeling
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
Published2014
Admission routes1
Has abstractyes

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Same topicNuclear Materials and PropertiesFrench-language works237,207