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Record W4205647301 · doi:10.1002/batt.202200007

Cover Feature: Spinel Type Mn−Co Oxide Coated Carbon Fibers as Efficient Bifunctional Electrocatalysts for Zinc‐Air Batteries (Batteries & Supercaps 2/2022)

2022· article· en· W4205647301 on OpenAlex
Zahra Abedi, Desirée Leistenschneider, Weixing Chen, Douglas G. Ivey

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBatteries & Supercaps · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBifunctionalSpinelZincMaterials scienceChemical engineeringCarbon fibersOxideFossil fuelSubstrate (aquarium)CoalMetallurgyNanotechnologyWaste managementChemistryComposite materialCatalysisEngineeringOrganic chemistryGeology

Abstract

fetched live from OpenAlex

The Cover Feature illustrates that asphaltene, an oil sands by-product typically used for road making, can be used as a conductive substrate for effective Mn−Co based bifunctional electrocatalysts in zinc-air batteries. A by-product, commonly associated with the negative environmental impact of fossil fuels, has been repurposed as part of the solution to our dependence on these fuels. More information can be found in the Research Article by D. G. Ivey and co-workers.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.253
Teacher spread0.239 · 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