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Record W2280654402 · doi:10.2217/whe.15.101

The Potential Influence of the Microbiota and Probiotics on Women during Long Spaceflights

2016· article· en· W2280654402 on OpenAlexaff
Camilla Urbaniak, Gregor Reid

Bibliographic record

VenueWomen s Health · 2016
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsCrewMicrobiomeSpace (punctuation)MedicineIntensive care medicineAeronauticsBioinformaticsEngineeringBiologyComputer science

Abstract

fetched live from OpenAlex

Humans have been exploring space for almost 55 years but space travel comes with many psychological and physiological changes that astronauts have to adapt to, both during and post flight missions. Now, with the reality of such missions lasting years, maintaining proper health of the flight crew is a high priority. While conditions such as nausea, bone loss, renal calculi and depression have been recognized, and approaches to medical and surgical care in space considered, the influence of the microbiota could be of added significance in maintaining astronaut health. While probiotics have long been part of the Russian cosmonaut diet, their use for specific health concerns of women has not been assessed. In this article, we explore the ways in which the microbiome may influence the health of female astronauts during long space flights, and present a rationale for the use of probiotics.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.003
GPT teacher head0.237
Teacher spread0.233 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2016
Admission routes1
Has abstractyes

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