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"Semantic characteristics of acute and dull pain (on the materials of the mcgill pain questionnaire and the large explanatory dictionary of the Russian language edited by S.A. Kuznetsov)"

2018· article· en· W4405467130 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDiscourse Analysis and Cultural Communication
Canadian institutionsnot available
Fundersnot available
KeywordsMcGill Pain QuestionnairePsychologyRussian languageLinguisticsNatural language processingComputer scienceMedicinePhilosophyPhysical therapy

Abstract

fetched live from OpenAlex

"The problem of adequate verbalization of emotions, sensations and feelings is one of the most important in modern applied linguistics. It is urgent to create a database of units on different linguistic levels intended for such verbalization. It is important in interdisciplinary branches for the languages with different structure, primarily in clinical practice, since the accuracy of the diagnosis depends on the ability to verbalize the sensations. In particular, this applies to people with a high level of alexithymia, having significant difficulties with naming their feelings. Alexithymia is a specific cognitive characteristic of the individual, affecting the ability to perceive sensations, emotions and feelings, to recognize them and adequately verbalize. Alexithymia may be a predictor or be closely related to a number of psychosomatic disorders that need to be prevented in a timely manner to avoid complications, so it is relevant to develop a linguistically valid psychometric diagnostic toolkit that is currently missing for alexithymic patients on the material of Russian language. This article is devoted to lexical units in the Russian language which are used for pain description. The authors analyze descriptors traditionally included in clinical questionnaires for the diagnosis of pain syndromes based on the explanations presented in the Large Russian Explanatory Dictionary of the Russian Language, ed. PP.A.Kuznetsov, analyze them from the point of view of semantics, paying special attention to such important and diagnostically important types of pain as acute and dull, discuss analytical data on results of the survey in patients who had pain complaints conducted to determine the validity of the proposed verbal descriptors."

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.

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)0.007
metaresearch head score (Gemma)0.001
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 score0.586
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.067
GPT teacher head0.467
Teacher spread0.400 · 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