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Record W2263860257 · doi:10.5539/jmbr.v6n1p11

Why Only People and Apes are Ill with Common Cold? The Possible Role of Chromosomal Q-Heterochromatin Variability

2016· article· en· W2263860257 on OpenAlexvenueno aff
A. I. Ibraimov

Bibliographic record

VenueJournal of Molecular Biology Research · 2016
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsCommon coldEtiologyImmunologyBiologyMedicinePathology

Abstract

fetched live from OpenAlex

Common cold (CC) is referred to the most widespread human illnesses and affects people all over the globe. Till now there is no standard theory explaining the development mechanism(s) of СС. The etiology of the CC is known - over 200 virus strains are implicated in the cause of the common cold; the rhinoviruses are the most common. As for pathogenesis, it is conventional, that cold plays the important role in development of СС. It is believed that cooling causes blood circulatory disturbance and permeability of vessels that consequently deteriorates the tissue nutrition and its resistance against infectious agents, and its resistibility in relation to infection. It is also known that the CC sickness rate is affected by the age (children get sick more often than adults) and gender (male individuals are more susceptible to CC than females, regardless of their age). Among the issues that have not received an answer is another question: why CC affects only upon humans and apes? It is hypothesized that the cause of these higher primates susceptibility to CC is the highest level of their body heat conductivity in the animal world. Just this circumstance contributes to the rapid and deep cooling of the bodies of people and apes when it is cold, with all the ensuing negative consequences for the organism.

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)0.003
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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.020
GPT teacher head0.347
Teacher spread0.327 · 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
Published2016
Admission routes1
Has abstractyes

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