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Record W2157717555 · doi:10.4021/jocmr2009.10.1267

The Unstimulated Salivary Flow Rate in a Jordanian Healthy Adult Population

2009· article· en· W2157717555 on OpenAlexvenueno aff
Faleh Sawair

Bibliographic record

VenueJournal of Clinical Medicine Research · 2009
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSalivaUnivariate analysisBody mass indexPopulationMultivariate analysisPopulation studyDentistryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Early diagnosis of xerostomia is very important for oral health. The purpose of this study was to determine the unstimulated whole salivary flow rates (UWSFR) in a Jordanian Arab population aged 15 years and older. The effect of age, gender, height, weight, body mass index (BMI), smoking, alcohol consumption, and dental conditions, on UWSFR was also investigated. METHODS: The study was conducted on 244 subjects, 110 males and 134 females, with an average age of 33 ± 15.5 years. They were healthy, unmedicated, and with no history of dry mouth. Unstimulated whole saliva was collected during five minutes, and UWSFRs (ml/min) were determined. Data were analyzed by univariate analysis and multivariate regression analysis. RESULTS: The mean UWSFR was 0.46 ± 0.25 ml/min (range: 0.10-1.6 ml/min). Eighteen patients (7.4%) had UWSFR between < 0.20 ml/min. In univariate analysis, UWSFR was significantly affected by age, BMI, number of missing and restored teeth, and DMFT score. Regression analysis revealed that only age and number of missing teeth were of significance in explaining the variability of the UWSFR. CONCLUSIONS: We established basic standard values of UWSFR to be used in the evaluation of Jordanian patients with complaints of xerostomia and to be compared to data reported in other studies. UWSFR 0.1 ml/min could be considered the cut-off value that distinguishes normal from abnormal salivary function in this healthy unmedicated population. KEYWORDS: Whole saliva flow rate; Unstimulated; Jordan.

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)0.013
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.194
GPT teacher head0.552
Teacher spread0.358 · 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 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

Citations28
Published2009
Admission routes1
Has abstractyes

Explore more

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