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Record W4385724613 · doi:10.1002/celc.202300348

Front Cover: An Insight into Synthesis of the Antifreeze Alkaline Hydrogel Electrolyte: Fine‐Tuning Chemistries for Efficient Ion Transport (ChemElectroChem 16/2023)

2023· paratext· en· W4385724613 on OpenAlexaff
Chun Keat Khor, Chance Coady Blackstone, Anna Ignaszak

Bibliographic record

VenueChemElectroChem · 2023
Typeparatext
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsElectrolyteIonic conductivityFront coverConductivityMaterials scienceIonNanotechnologyCover (algebra)Chemical engineeringEnvironmental scienceComputer scienceElectrodeChemistryMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

The Front Cover illustrates the structure of a leakage-free polymer electrolyte that sustains its ionic conductivity and mechanical resilience at extremely cold temperature. This article evaluates chemical compatibility among the hydrogel components with a goal to develop temperature-resistant electrolyte that can satisfy the application requirements in wearable electronics. The flexible and stretchable electrolyte that endures strain without being damaged and yet is operational within the user's range of motion must reliably function under varied and extreme temperature conditions, particularly in persistent cold climates. Cover design was created by Ella Maru Studio. More information can be found in the Research Article by C. K. Khor et al.

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 score0.057
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0570.024

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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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