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Record W2915337532 · doi:10.1002/marc.201770005

Macromol. Rapid Commun. 2/2017

2017· article· en· W2915337532 on OpenAlexaff
Ye Sha, Dongliang Qi, Shaochuan Luo, Xinghua Sun, Xiaoliang Wang, Gi Xue, Dongshan Zhou

Bibliographic record

VenueMacromolecular Rapid Communications · 2017
Typearticle
Languageen
FieldEngineering
TopicGraphene and Nanomaterials Applications
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsQuantum entanglementFörster resonance energy transferPolymerScalingFront coverPolymer scienceChain (unit)Cover (algebra)Materials scienceNanotechnologyPolymer chemistryPhysicsFluorescenceOpticsMathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

Front Cover: FRET dyes are dictated into separate polymer chain centers by site-specific ATRP quantitatively, which allows for characterization of the well-defined interchain distance quantitatively based on the FRET response. This well-defined FRET system is expected to be a promising candidate to provide a distinct physical image at a microscopic level regarding scaling chain dimension, chain interpenetration, chain entanglement and polymer compatibility. Further details can be found in the article by Y. Sha, D. Qi, S. Luo, X. Sun, X. Wang, G. Xue,* and D. Zhou* in article 1600568.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.690
Threshold uncertainty score0.985

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.3100.203

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 head0.029
GPT teacher head0.265
Teacher spread0.236 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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