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Record W4322748025 · doi:10.5114/jos.2023.125012

Role of nanotechnology in dentistry:a systematic review

2023· review· en· W4322748025 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Stomatology · 2023
Typereview
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDentistry

Abstract

fetched live from OpenAlex

ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Raj A, J. Shetty N, Atif A. Role of nanotechnology in dentistry: a systematic review. Journal of Stomatology. 2023. doi:10.5114/jos.2023.125012. APA Raj, A., J. Shetty, N., & Atif, A. (2023). Role of nanotechnology in dentistry: a systematic review. Journal of Stomatology. https://doi.org/10.5114/jos.2023.125012 Chicago Raj, Akanksha, Neetha J. Shetty, and Ali Atif. 2023. "Role of nanotechnology in dentistry: a systematic review". Journal of Stomatology. doi:10.5114/jos.2023.125012. Harvard Raj, A., J. Shetty, N., and Atif, A. (2023). Role of nanotechnology in dentistry: a systematic review. Journal of Stomatology. https://doi.org/10.5114/jos.2023.125012 MLA Raj, Akanksha et al. "Role of nanotechnology in dentistry: a systematic review." Journal of Stomatology, 2023. doi:10.5114/jos.2023.125012. Vancouver Raj A, J. Shetty N, Atif A. Role of nanotechnology in dentistry: a systematic review. Journal of Stomatology. 2023. doi:10.5114/jos.2023.125012.

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.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.115
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.060
GPT teacher head0.422
Teacher spread0.362 · 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