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Record W2887032304 · doi:10.1080/20002297.2018.1495975

<i>In situ</i>substrate-formed biofilms using IDODS mimic supragingival tooth-formed biofilms

2018· article· en· W2887032304 on OpenAlexfundno aff
Inmaculada Tomás, Isabel Prada-López, Victor Quintas, Marı́a J. Carreira, Áurea Simón‐Soro, Álex Mira, Carlos Balsa‐Castro

Bibliographic record

VenueJournal of Oral Microbiology · 2018
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsnot available
FundersFaculty of Medicine and Dentistry, University of AlbertaXunta de GaliciaInstituto de Salud Carlos IIIFederación Española de Enfermedades Raras
KeywordsBiofilmEnamel paintMicrobiologyDentistryChemistryDental plaqueBacteriaBiologyMedicine

Abstract

fetched live from OpenAlex

to a supragingival tooth-formed biofilm (TF-biofilm) in the same group of individuals. The impact of the device/disc position and toothbrushing during the formation of SF-biofilm was also assessed. Two tests were run. In test 1, 15 volunteers wore two hemi-splints carrying six discs of human enamel, glass, and hydroxyapatite for 2 days, and were instructed to not perform any oral hygiene measure. Biofilm samples were collected from the substrates and the contralateral tooth and were analysed using CLSM. In five volunteers, half of the biofilm present on the discs and their contralateral teeth were scraped and analysed using 16S pyrosequencing. In test 2, the microscopic analysis was repeated only on the SF-biofilm samples, and the volunteers were allowed to brush their teeth. Multivariate analyses revealed that the donors had a significant effect on the composition of the biofilm, confirming its subject-dependent character. The bacterial composition of the SF-biofilm was similar to the TF-biofilm, with significant differential abundance detected in very few taxa of low abundance. The toothbrushing during the formation of SF-biofilm was the only factor that conditioned the thickness or bacterial viability.

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)0.001
metaresearch head score (Gemma)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.040
GPT teacher head0.337
Teacher spread0.297 · 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 designBench or experimental
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

Citations5
Published2018
Admission routes1
Has abstractyes

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