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Record W7066429272

Indicators of quality of life and adaptation to chronic tense headaches

2012· article· en· W7066429272 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsQuality of life (healthcare)HeadachesAdaptation (eye)Chronic painLife qualityQuality (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

The goal of the research is the comparative analysis of a quality of life and quantitative characteristics of a chronic tense headache as well as the studying of adaptive reactions. 123 women (middle age 42,6±2,3) with initiatory stages of chronic tense headaches have been examined using diagnostic criteria of the International classifcation of headache disorders (ICDH — II, 2003), headache diary and the McGill Pain Questionnaire. Headache intensity was estimated by the Visual Analog Scale. Monitoring quality of life (QOL) was organized in a form of a questionnaire SF-36. An adaptive reactions type was analizing by L. Kh. Garkavi. Clinical implications and quantitative characteristics of a chronic tense headache, condition of vegetative and emotional sphere, and also quality of life and adaptive reactions are studied. Infuence of chronic headache on various components quality of life was investigated. Monitoring of physical, psychological and social functioning of patients with reception of differential and integrated quantity indicators of QOL, and also the analysis of adaptic reactions will give the chance to the doctor to develop a complex of practical references on treatment chronic tense headache at patients with poor quality of life and adverse adaptive reactions.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.423
GPT teacher head0.538
Teacher spread0.115 · 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
Published2012
Admission routes1
Has abstractyes

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