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Record W2678969369 · doi:10.15214/jsodom.30.176

The Relationship between Temporal Changes in Subjective Symptoms, Mental States and Sensory Thresholds after Inferior Alveolar Nerve Injury

2017· article· en· W2678969369 on OpenAlexaboutno aff
Akiko Kobayashi, M. Mochizuki, Junya Kumagai

Bibliographic record

VenueJapanese Journal of Oral Diagnosis / Oral Medicine · 2017
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsAudiologySensory systemAnxietySensory thresholdDepression (economics)SensationStimulus modalityPsychologyPerceptionMedicinePsychiatryNeuroscienceCognitive psychology

Abstract

fetched live from OpenAlex

This study investigated relationships between changes in sensory thresholds, subjective symptoms, and mental states over time in 55 patients who had sensory disturbances on their unilateral lower lip and chin.The sensory thresholds were determined by nine different testing modalities which included static light touch, two-point discrimination, warm/cool/heat stimulation, 5-Hz rectangular current stimulation, and current perception thresholds (2,000Hz, 250Hz, 5Hz). Obtained thresholds were classified into five scores (0–4), and the average of the scores for all the tests was calculated as the individual score (average score).To investigate what kind of subjective sensations the patients were experiencing, the McGill Pain Questionnaire (Japanese version) was applied. The degree of hindrance in daily life, degree of subjective sensory abnormality, and daily duration of sensory disturbance were investigated using visual analog scales. To investigate the patient's mental state, we used the Hospital Anxiety and Depression Scale.Neither the changes in subjective symptoms nor the mental states of anxiety and depression showed a significant correlation with recovery in sensory thresholds (i.e., the average scores). The changes in patients' subjective symptoms and mental states were not associated with the appearance/disappearance of hypersensitivity to thermal stimulation or current perception thresholds.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.358
Teacher spread0.286 · 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 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
Published2017
Admission routes1
Has abstractyes

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