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Record W4387237139 · doi:10.4317/jced.60816

J Clin Exp Dent

2023· article· en· W4387237139 on OpenAlexaboutno aff
J. Sasikala, J R Sukhabogi, Dolar Doshi, Turaga Sai Susmitha, B. Lakshmi

Bibliographic record

VenueJournal of Clinical and Experimental Dentistry · 2023
Typearticle
Languageen
FieldHealth Professions
TopicDental Education, Practice, Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePain catastrophizingCoping (psychology)Physical therapyActivities of daily livingPopulationCorrelationChronic painClinical psychology

Abstract

fetched live from OpenAlex

Background: Physical disability results in impaired mobility, leading to increased dependency on others and may also have a negative impact on ones general and oral health. Moreover, such individuals could be at a greater risk of being prone to chronic pain conditions. A person's ability to cope with pain is a consistent and one of the most important predictors of clinical outcome. Catastrophization is known to be a maladaptive coping behaviour that could negatively influence such outcomes. Material and Methods: A cross-sectional study was conducted among 229 physically disabled individuals at Home for Disabled, Bansilalpet, Secunderabad. Extent of Physical disability was measured using Barthel index of Activities of Daily Living (ADL), type and severity of dental pain was assessed using the short form McGill Pain Questionnaire and catastrophizing using the Pain Catastrophizing Scale (PCS). Dentition status and periodontal status were assessed using the World Health Organization assessment form. Results: <0.05) correlation with sensory pain(r=0.182), visual analog scale(r=0.168), pain severity(r=0.161) and DMFT (r=0.4). It had significant negative correlation with ADL and bleeding gums. Conclusions: Disability, Oral Health, Catastrophizing.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.329
GPT teacher head0.668
Teacher spread0.339 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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