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Record W2979531394 · doi:10.1002/anie.201984261

Frontispiece: Building a Bridge from Papermaking to Solar Fuels

2019· paratext· en· W2979531394 on OpenAlexaff
Zaiyong Jiang, Xinhan Zhang, Wei Sun, Deren Yang, Paul N. Duchesne, Yugang Gao, Zeyan Wang, Tingjiang Yan, Zhimin Yuan, Guihua Yang, Xingxiang Ji, Jiachuan Chen, Baibiao Huang, Geoffrey A. Ozin

Bibliographic record

VenueAngewandte Chemie International Edition · 2019
Typeparatext
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPapermakingBridge (graph theory)Joint ventureGraphenePhotocatalysisSolar energyMaterials scienceRenewable energyEngineeringNanotechnologyEnvironmental scienceEngineering physicsWaste managementPolymer scienceComposite materialChemistryElectrical engineeringBusinessOrganic chemistry

Abstract

fetched live from OpenAlex

Solar Fuels The preparation of graphene quantum dots from black liquor is reported by W. Sun, J. Chen, G. A. Ozin et al. in their Communication on page 14850 ff. The obtained GQDs were exploited to improve the photocatalytic H2O and CO2 reduction activities of TiO2.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.248
Threshold uncertainty score0.831

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.2480.195

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 head0.018
GPT teacher head0.304
Teacher spread0.286 · 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
Published2019
Admission routes1
Has abstractyes

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