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Record W3043444450 · doi:10.2485/jhtb.29.165

Relationship between Oral Function and Occlusal Bite Force in the Elderly

2020· article· en· W3043444450 on OpenAlexaff
Naoko Imagawa, Nahoko Kato‐Kogoe, Kei Suzuki, Michi Omori, Yoshifumi Suwa, Kazuya Inoue, Hiroyuki Nakano, Kayoko Yamamoto, Kuniyasu Kamiya, Satoyo Ikehara, Masaaki Hoshiga, Junko Tamaki, Ryo Kawata, Takaaki Ueno

Bibliographic record

VenueJournal of Hard Tissue Biology · 2020
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsUniversity of British Columbia
FundersJapan Society for the Promotion of Science
KeywordsMasticatory forceMedicineDentistryBite force quotientTongueOrthodonticsOral examinationMasticationOral health

Abstract

fetched live from OpenAlex

The goal of hard tissue reconstruction in the oral and maxillofacial field is good oral function. However, research into oral function remains inadequate and methods for evaluating oral function have yet to be established. In this study, we report the relationship between oral function and occlusal bite force in the elderly. This study included 108 residents of Takatsuki City aged 60 years or older. Oral condition was assessed by measuring tooth loss and periodontal condition, and oral function was assessed based on masticatory performance indicators. Mean age was 75.5±4.8 years. As indicators of occlusal function, the means of maximum occlusal force, gummy jelly score (masticatory performance score) and time required for 30 chews were 313.5±234.8 N, 4.0 and 28.5±10.0 s, respectively. As indicators of oral function, the means of tongue pressure, salivary flow rate and lip pressure were 26.3±8.9 kPa, 1.5±0.93 g/min and 12.7±7.1 N, respectively. In this study, we report mean values for oral function in healthy elderly subjects. In the future, it will be necessary to clarify standard values for residents with various diseases.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.221

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.148
GPT teacher head0.438
Teacher spread0.291 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2020
Admission routes1
Has abstractyes

Explore more

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