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Record W37496678 · doi:10.1016/j.isci.2023.107275

Nové čísla e-bulletinu MEFANETin

2012· article· en· W37496678 on OpenAlexfundno aff
Michal Trnka

Bibliographic record

VenueiScience · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, Psychology, and Social Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsComputer scienceBusiness

Abstract

fetched live from OpenAlex

Active components with suitable supports are the common paradigm for industrial catalysis, and the catalytic activity usually increases with minimizing the active component size, generating a new frontier in catalysis, single-atom catalysts (SACs). However, further improvement of SACs activity is limited by the relatively low loading of single atoms (SAs, which are heteroatoms for most SACs, i.e., external active sites) because of the highly favorable aggregation of single heteroatoms during preparation. Research interest should be shifted to investigate SACs with intrinsic SAs, which could circumvent the aggregation of external SAs and consequently increase the SAs loading while maintaining them individual to further improve the activity. In this review, SACs with external or intrinsic SAs are discussed and, at last, the perspectives and challenges for obtaining high-loading SACs with intrinsic SAs are outlined.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.754
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.109
GPT teacher head0.499
Teacher spread0.390 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2012
Admission routes1
Has abstractyes

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