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Record W3039912283 · doi:10.1017/s1431927600035844

Bacterial Attachment to Oral Epithelium

2000· article· en· W3039912283 on OpenAlexaboutno aff
Ljubomir Vitkov, Wolf Dietrich Krautgartner, Matthias Hannig, K.-H. Fuchs

Bibliographic record

VenueMicroscopy and Microanalysis · 2000
Typearticle
Languageen
FieldMedicine
TopicNasal Surgery and Airway Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOsmium tetroxideGlutaraldehydeEpitheliumStomatitisChemistryOral mucosaPathologyRuthenium redMedicineChromatographyElectron microscopeInternal medicine

Abstract

fetched live from OpenAlex

Abstract The purpose of this work was to examine, by electron microscopy, the mechanism of bacterial binding to oral epithelium in patients with stomatitis using ruthenium red in combination with osmium tetroxide. Bacteriological semi-quantitative estimation of smear from the palatal mucosa was performed in patients with stomatitis and only patients with viridans Streptococci were further included in the present investigation. Biopsies were taken from the inflamed keratinizing mucosa under regional block anesthesia in agreement with Vancouver guidelines 1978. Control samples were fixed with 1.2% glutaraldehyde (buffered at pH 6.5 with 0.1 M sodium cacodylate) for 2 h at 4° C. Postfixation was performed with 1% osmium tetroxide (buffered at pH 6.5 with 0.1 M sodium cacodylate) for 2 h at 4° C. The other samples were fixed and postfixed by the fixatives mentioned before with addition of 1.6 % ruthenium red in each case.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.292
Teacher spread0.279 · 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 designObservational
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

Citations1
Published2000
Admission routes1
Has abstractyes

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