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Record W4288082210 · doi:10.1039/d2tc90147a

Correction: XSnS<sub>3</sub> (X = Ga, In) monolayer semiconductors as photo-catalysts for water splitting: a first principles study

2022· article· en· W4288082210 on OpenAlexafffund
Mosayeb Naseri, Dennis R. Salahub, Tuan V. Vu, Zakaryae Haman

Bibliographic record

VenueJournal of Materials Chemistry C · 2022
Typearticle
Languageen
FieldEngineering
TopicChalcogenide Semiconductor Thin Films
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMonolayerMaterials scienceSemiconductorWater splittingCatalysisNanotechnologyPhotocatalysisOptoelectronicsChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Correction for ‘XSnS 3 (X = Ga, In) monolayer semiconductors as photo-catalysts for water splitting: a first principles study’ by Mosayeb Naseri et al. , J. Mater. Chem. C , 2022, https://doi.org/10.1039/d2tc01613c.

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)0.003
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.044
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0510.029

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 head0.017
GPT teacher head0.221
Teacher spread0.204 · 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 designSimulation or modeling
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

Citations3
Published2022
Admission routes2
Has abstractyes

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Same venueJournal of Materials Chemistry CSame topicChalcogenide Semiconductor Thin FilmsFrench-language works237,207