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Record W4386762152 · doi:10.1002/9781394167197.ch14

Natural Oral Care Therapy for Peri‐Implant Diseases

2023· other· en· W4386762152 on OpenAlexaff
Bharat Mirchandani, Hans Erling Skallevold, Artak Heboyan, Diane Isabel Selvido, Viritpon Srimaneepong, Pasutha Thunyakitpisa, Dinesh Rokaya

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPeri-implantitisMucositisMedicinePeriodontitisImplantImplant failureDentistryBleeding on probingPathologicalPathologySurgeryRadiation therapy

Abstract

fetched live from OpenAlex

Peri-implantitis is a serious complication around the dental implant in the mouth. There has been increasing evidence of peri-implantitis resulting clinical failure and ultimately loss of the implant. Peri-implantitis, as chronic periodontitis, is commenced and maintained in the presence of a spectrum of pathogens, and presents with comparable symptoms and findings, pathological probing depths and bleeding on probing, including similar microbiology. Plaque accumulation and biofilm formation, dominated by Gram negative anaerobes, after implant placement are components to induce and advance the disease. This inflammatory response can result in the clinical findings of peri-implant mucositis, and irreversible destruction of tissues as evident in peri-implantitis. Various herbal extracts can be utilized in the management of peri-implantitis. This chapter presents an overview of peri-implantitis and natural care therapy including various herbal products used for the management of the peri-implantitis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.004

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 head0.377
Teacher spread0.344 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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