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Record W2138794673 · doi:10.4172/2376-0281.1000137

Personality Variables in Prediction of Control over Seizures in Patients with Partial Epilepsies

2014· article· en· W2138794673 on OpenAlexaboutno aff
Vladimir V Kalinin Anna A Zemlyanaya

Bibliographic record

VenueInternational Journal of Neurorehabilitation · 2014
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPersonalityOmicsEpilepsyMedicinePsychologyClinical psychologyPsychiatryBioinformaticsBiologySocial psychology

Abstract

fetched live from OpenAlex

The current study has been carried out in order to evaluate the possible relationship between premorbid personality constructs with therapeutic remission and seizures reduction under antiepileptic treatment in patients with partial forms of epilepsy. One hundred and three patients were included into study. There were 33 men and 70 women. The Munich Personality Test and Toronto Alexithymia Scale (TAS-26) have been used for the assessment of premorbid personality in patients. Product moment correlation and multiple forward stepwise regression were used for the analysis of interrelationship between independent variables (personality constructs) and dependent variables of therapeutic remission and percentage in seizures reduction. Obtained results have shown the favorable prognostic significance of Neuroticism, Extraversion, Frustration Tolerance for the percentage of sum of all partial seizures reduction and for sensory partial and motor partial seizures reduction. On the other hand, alexithymia correlated negatively with length of remission and percentage of all seizures reduction.

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)0.000
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 score0.010
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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