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Record W4315779418 · doi:10.1038/s41560-022-01188-2

Energy- and carbon-efficient CO2/CO electrolysis to multicarbon products via asymmetric ion migration–adsorption

2023· article· en· W4315779418 on OpenAlex
Adnan Ozden, Jun Li, Sharath Kandambeth, Xiaoyan Li, Shijie Liu, Osama Shekhah, Pengfei Ou, Y. Zou Finfrock, Ya‐Kun Wang, Tartela Alkayyali, F. Pelayo Garcı́a de Arquer, Vinayak S. Kale, Prashant M. Bhatt, Alexander H. Ip, Mohamed Eddaoudi, Edward H. Sargent, David Sinton

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNature Energy · 2023
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsUniversity of Toronto
FundersCanadian Light SourceNatural Sciences and Engineering Research Council of CanadaGeneralitat de CatalunyaArgonne National LaboratoryU.S. Department of EnergyCentres de Recerca de Catalunya“la Caixa” FoundationAgencia Estatal de InvestigaciónOffice of ScienceCanada Research ChairsNatural Resources CanadaOntario Research Foundation
KeywordsElectrolysisCatalysisCarbon fibersAdsorptionChemical engineeringInorganic chemistryMaterials scienceChemistryElectrodeOrganic chemistryElectrolyte

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)
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 score0.247
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.232
Teacher spread0.227 · 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