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Record W2916049717 · doi:10.1002/marc.201870024

Macromol. Rapid Commun. 10/2018

2018· article· en· W2916049717 on OpenAlexaff
Liu Leo Liu, Sha Luo, Qing Yan, Ning Yan, Yiqiang Wu, Xinfeng Xie, Feiyu Hu

Bibliographic record

VenueMacromolecular Rapid Communications · 2018
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPolyanilineMaterials scienceElectrical conductorSubstrate (aquarium)Front coverConductivityConductive polymerPolymerizationPolymer chemistryNanotechnologyCover (algebra)Chemical engineeringComposite materialPolymerChemistryMechanical engineering

Abstract

fetched live from OpenAlex

Front Cover: In article number 1700836, Yan Qing, Yiqiang Wu, and co-workers report a linearly tunable electronic conductive hydrogel prepared by in-situ-polymerized polyaniline (PANI) on a CNFs/MEO2MA/PEGMA substrate. This intelligent and flexible hydrogel exhibits temperature-tunable electric conductivity from 20 °C to 65 °C. Based on this favourable feature, a facile and sensitive temperature sensor with PANI@CMP hydrogel as induction body is fabricated as a smart temperature monitor.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.724
Threshold uncertainty score0.923

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.2760.200

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 head0.040
GPT teacher head0.296
Teacher spread0.256 · 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.

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

Citations1
Published2018
Admission routes1
Has abstractyes

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