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18th International Conference on Textures of Materials (ICOTOM-18)

2018· article· en· W4236862678 on OpenAlexaboutno aff

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)Library scienceHumanitiesArtArt history

Abstract

fetched live from OpenAlex

Preface The 18th International Conference on Textures of Materials (ICOTOM 18) took place in St George, Utah, USA, November 5-10, 2017. ICOTOM-18 follows in the long “triennial” tradition of ICOTOM meetings initiated in 1969 in Clausthal, Germany and followed with: Cracow (1971), Pont-à-Mousson (1973), Cambridge (1975), Aachen (1978), Tokyo (1981), Noordwijkerhout (1984), Santa Fe (1987), Avignon (1990), Clausthal (1993), Xian (1996), Montreal (1999), Seoul (2002), Leuven (2005), Pittsburgh (2008), Mumbai (2011), Dresden (2014). ICOTOM-18 continued the fine scientific tradition of previous ICOTOMs fostering the fundamental understanding of the basic processes underlying the formation of texture and its relation to the anisotropic properties of polycrystalline materials. One of the motivating factors for holding ICOTOM in Utah was the long-standing contributions of Professor Brent L. Adams to the texture community. Professor Adam’s spent much of his life and professional career in Utah. Brent’s work in linking crystallographic orientation to microstructure led to the automation of Electron Backscatter Diffraction or EBSD, with seminal journal papers appearing 25 years before ICOTOM 18. The entire texture community has been instrumental in the incubation of this technology and the continued cultivation of both its development and application. With EBSD and other techniques providing textural information from the nano to the macro scale, our understanding of the links between the local orientation and texture evolution and material properties continues to grow. ICOTOM-18 provided a forum for both materials scientists and geologists to engage in the discussion of recent progress in texture and anisotropy research.

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 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 categoriesScholarly communication, Insufficient payload (model declined to judge)
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 score0.196
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.051
GPT teacher head0.247
Teacher spread0.196 · 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 teacher head, not a consensus.

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
Published2018
Admission routes1
Has abstractyes

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