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Record W4231870944 · doi:10.1515/ntrev.2011.001

Probing nanoscale behavior of magnetic materials with soft X-ray spectromicroscopy

2011· article· en· W4231870944 on OpenAlexfundno aff
Peter Fischer, C. S. Fadley

Bibliographic record

VenueNanotechnology Reviews · 2011
Typearticle
Languageen
FieldMaterials Science
TopicMultiferroics and related materials
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceNanocompositeComposite materialPolydimethylsiloxaneModulusYoung's modulusCarbon nanotubeElastic modulusCastingElastomer

Abstract

fetched live from OpenAlex

The Nanotechnology Reviews (NTREV) journal aims at all aspects of nano-science and nano-engineering as well as emerging innovative topics of all areas of engineering science at the nanoscale , nano-energy , nano-biomaterials , and nano-composites . The journal emphasizes interdisciplinary and multi-functional research and linkage between nanotechnology and composites technology . Non-nano papers with potential significant future contributions to nano-research may be welcomed on a case by case basis. These topics include: bio-inspired/soft materials , 3D/4D printing , molecular dynamics/multi-scale modeling , imaging , batteries , graphene/carbon nano tubes , nano-mechanics , and many others. Check out the latest table of contents at a glance with easy access to most cited and most downloaded Nanotechnology Reviews’ papers of 2020 and 2021 ! Table of contents 2020 Table of contents 2021

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · 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)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.028
GPT teacher head0.255
Teacher spread0.228 · 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
GenreReview

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

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