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Record W4389351957 · doi:10.1039/d3na90118a

Contents list

2023· article· it· W4389351957 on OpenAlexfundno aff

Bibliographic record

VenueNanoscale Advances · 2023
Typearticle
Languageit
FieldComputer Science
TopicDigital Media and Visual Art
Canadian institutionsnot available
FundersUniversity of California, Los AngelesUniversity of Illinois at Urbana-ChampaignSouthern University of Science and TechnologyWuhan UniversityUniversidade de VigoNational Chemical LaboratorySouthwest UniversityTsinghua UniversityJilin UniversityIndian Institute of Technology MadrasDalhousie UniversityBeijing University of Chemical TechnologyUlsan National Institute of Science and TechnologyQueensland University of TechnologyUniversity of PennsylvaniaÉcole Polytechnique Fédérale de LausanneMcMaster UniversityMax-Planck-Institut für PolymerforschungChinese Academy of SciencesIndian Institute of ScienceUniversity of Nebraska-LincolnUniversity of SydneyEwha Womans UniversityUniversity of BathPennsylvania State UniversityCarnegie Mellon UniversityUniversity of Science and Technology of ChinaNanyang Technological UniversityAarhus UniversitetNanjing Normal UniversityUniversity of California, San DiegoSeoul National UniversityNational Institute for Materials ScienceCurtin University of TechnologyMonash UniversityCity University of Hong KongWayne State UniversityUniversity of WashingtonBrown University
KeywordsAcknowledgementAttributionComputer scienceChromatin structure remodeling (RSC) complexWorld Wide WebLibrary scienceComputer securityPsychologyChemistrySocial psychology

Abstract

fetched live from OpenAlex

Permissions Request permissions Contents list Nanoscale Adv., 2023, 5, 6741 DOI: 10.1039/D3NA90118A This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given. Read more about how to correctly acknowledge RSC content.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.007

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 head0.034
GPT teacher head0.309
Teacher spread0.275 · 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 teacher head, not a consensus.

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
Published2023
Admission routes1
Has abstractyes

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