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Record W4388204546 · doi:10.3329/jbcps.v41i4.66936

Oral Potentially Malignant Disorders: A review on Bangladesh perspective

2023· review· en· W4388204546 on OpenAlexaff
Mushfiq Hassan Shaikh, Md Ashif Iqbal, SM Anwar Sadat

Bibliographic record

VenueJournal of Bangladesh College of Physicians and Surgeons · 2023
Typereview
Languageen
FieldDentistry
TopicOral Health Pathology and Treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineLeukoplakiaOral lichen planusOral submucous fibrosisArecaDermatologyOral mucosaCancerPopulationEpithelial dysplasiaInternal medicinePathologyEnvironmental health

Abstract

fetched live from OpenAlex

Oral potentially malignant disorders (OPMDs) are a group of chronic conditions affecting the oral mucosa with a risk of transformation to oral squamous cell carcinoma (OSCC). Oral leukoplakia, oral submucous fibrosis, oral lichen planus, and oral erythroplakia are the most common OPMDs observed in South Asian population. However, oral leukoplakia and oral lichen planus are commonly encountered OPMDs in clinical practice in Bangladesh, possibly, owing to specific lifestyle habits. Although the exact aetiology is unknown, use of smokeless tobacco, smoking, and chewing of betel quid containing areca nut, are considered as common risk factors for OPMDs. Early diagnosis is very important and can be lifesaving, as at a late stage, OPMDs are more likely to progress into severe dysplasia or even into squamous cell carcinoma. In fact, OPMDs have a significantly increased risk of progressing to cancer, mostly in South Asian population, including Bangladesh. This review provides an overview of the OPMDs in Bangladeshi population. J Bangladesh Coll Phys Surg 2023; 41(4): 305-314

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.041
GPT teacher head0.352
Teacher spread0.311 · 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
GenreReview

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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