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Record W4407045656 · doi:10.61760/18290108-ehs24.2-100

Վիրավորների օրգանիզմի հարմարվողական պրոցեսների ռեակտիվության նվազման դերը թոքաբորբերի զարգացման գործում / The role of reducing reactivity of adaptive processes in the body of the wounded in the development of pneumonias

2024· article· en· W4407045656 on OpenAlexaff
M. V. Sargsyan, Arik Melikyan, G. S. Datumyan, Ludwig Petrosyan, H. A. Melikyan

Bibliographic record

VenueՀայկական բանակ / Armenian Army · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMedicinal Plants and Bioactive Compounds
Canadian institutionsCanadian College of Massage and Hydrotherapy
Fundersnot available
KeywordsReactivity (psychology)MedicineIntensive care medicinePathology

Abstract

fetched live from OpenAlex

Pulmonary and pleural diseases are the most common complications of wounds and injuries. The probability of occurrence of pneumonia and the changes of some clinical, biochemical and hormonal indicators among the military, aged 18-25, have been analyzed in this article from the viewpoint of assessing the immune resistance of the body. Studies have shown that in case of the development of pneumonia of varied severity, similar changes in the hormonal composition of the blood can be detected: a relative increase in the levels of prolactin, a relative decrease in the levels of testosterone and a decrease in the levels of cortisol. Taking into account the paradoxical reaction of the endocrine glands revealed through this research, it can be concluded that among the examined patients, in conditions of unusual, overextended physical activity of the body, the influence of almost constant stress factors during the military service led to the exhaustion of adaptive resources. As a result, when wounded, the body was not ready for an adequate immune response, which also contributed to the development of pneumonia.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.257
Teacher spread0.241 · 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
Published2024
Admission routes1
Has abstractyes

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Same venueՀայկական բանակ / Armenian ArmySame topicMedicinal Plants and Bioactive CompoundsFrench-language works237,207