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Record W4393507313 · doi:10.5281/zenodo.3960529

Synchrotron Diffraction During Stress Relaxation in CP Ti (grade 4)

2020· dataset· en· W4393507313 on OpenAlexaff
A.J. Wilkinson, Xiong Yi, Phani Karamched, Christopher M. Magazzeni, Edmund Tarleton, David M. Collins, Chi-Toan Nguyen

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typedataset
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsSafran Electronics (Canada)
FundersResearch Councils UK
KeywordsSynchrotronStress relaxationMaterials scienceStress (linguistics)Relaxation (psychology)DiffractionCrystallographyPhysicsMetallurgyChemistryNuclear physicsOpticsMedicineInternal medicineCreep

Abstract

fetched live from OpenAlex

These data support the associated paper: Cold Creep of Titanium: Analysis of stress relaxation using synchrotron diffraction and crystal plasticity simulations Yi Xiong, Phani Karamched, Chi-Toan Nguyen, David M Collins, Christopher M Magazzeni, Edmund Tarleton, Angus J Wilkinson Acta Materialia (2020) vol. 199, 561-577 https://doi.org/10.1016/j.actamat.2020.08.010 The Authors' Accepted Manuscript version of the paper is available open access on arXiv: https://arxiv.org/ftp/arxiv/papers/2003/2003.01682.pdf This dataset arises from an in situ stress relaxation experiment on commercially pure (grade 4) Ti undertaken at the Diamond Light Source, beamline ID12, as part of experiment EE17222. The sample was loaded to just beyond the yield point, and then held at constant strain for 5 minutes over which time the stress relaxed. The sample was then reloaded elastically and a further period of stress relaxation at fixed total strain undertaken. in total five periods of stress relaxation were imposed. Throughout the mechanical testing cycle powder diffraction patterns were recorded in the transmission geometry, at 1 second intervals using a 2d Pixium detector held 1097 mm from the sample. The beam energy was determined to be 79.79 keV. Diffraction Patterns are contained as 16 bit TIF files bundled into the Patterns_72995.zip file. Macroscopic mechanical test data are in the excel file MechTest_2995.xlsx. Small EBSD map in #.ctf format converted from Bruker #bcf file in CPg4.ctf file. Matlab + MTEX script to load and make simple plots from EBSD data file in CPg4Ti_EBSDmap.m file. Details of the MTEX orientation analysis package from Matlab can be found and freely downloaded at: https://mtex-toolbox.github.io/

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0320.003

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 head0.023
GPT teacher head0.215
Teacher spread0.192 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

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