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Record W3044183415 · doi:10.1039/d0cc03556d

Water content in solid polymer electrolytes: the lost knowledge

2020· article· en· W3044183415 on OpenAlexafffund
Denis Mankovsky, David Lepage, Marie Lachal, Léa Caradant, David Aymé‐Perrot, Mickaël Dollé

Bibliographic record

VenueChemical Communications · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolymerElectrolyteWater contentPolymer electrolytesChemical engineeringContent (measure theory)ChemistryMaterials scienceOrganic chemistryGeologyEngineeringPhysical chemistryMathematicsIonic conductivity

Abstract

fetched live from OpenAlex

We reproducibly quantify the water content in different SPE systems through various processing/drying conditions and tie the residual amounts of water to heightened ionic conductivities. Moreover, we emphasise on the need to control the sample preparation and isolation as hydration occurs instantly when the dried sample encounters air.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.263
Teacher spread0.205 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations37
Published2020
Admission routes2
Has abstractyes

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