MétaCan
Menu
Back to cohort
Record W2902754383 · doi:10.1088/2053-2571/aae653

Novel Microstructures for Solids

2018· book· en· W2902754383 on OpenAlexaff
R. A. Dunlap

Bibliographic record

VenueMorgan & Claypool Publishers eBooks · 2018
Typebook
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsQuasicrystalContext (archaeology)MicrostructureAmorphous solidCarbon fibersMaterials scienceCrystallographyTranslational symmetryCrystal structureNanotechnologyChemistryPhysicsCondensed matter physicsComposite materialComposite numberGeology

Abstract

fetched live from OpenAlex

In the early part of the 20th century, x-rays were first used for the investigation of the atomic structure of solids. Until the 1980s experimental evidence suggested that virtually all solid materials were either amorphous or ordered three-dimensional structures with translational and rotational symmetry that were described by classical crystallographic concepts. Since then, a number of structures that stretch the concept of a crystalline material have been discovered. In 1984 a solid phase, known as a quasicrystal, that possessed long-range order but lacked the periodicity of a crystalline material, was observed. At about the same time, novel molecular structures were observed for elemental carbon, and more recently, carbon has been prepared as a two-dimensional material. Some of the recently discovered materials with novel microstructures are reviewed in the present book. Part I of the book describes the structure and properties of quasicrystalline materials while Part II gives an overview of some of the unique phases that have been observed for elemental carbon. These unusual structures are discussed in the context of related materials with traditional crystallographic order.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.007

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 head0.022
GPT teacher head0.263
Teacher spread0.241 · 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
GenreOther

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

Citations8
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueMorgan & Claypool Publishers eBooksSame topicBoron and Carbon Nanomaterials ResearchFrench-language works237,207