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Record W4399535260 · doi:10.1038/s41467-024-47237-0

Astronaut omics and the impact of space on the human body at scale

2024· article· en· W4399535260 on OpenAlexfundno aff
Lindsay Rutter, Henry Cope, Matthew MacKay, Raúl Herranz, Saswati Das, С. А. Пономарев, Sylvain V. Costes, Amber M. Paul, Richard Barker, Deanne Taylor, Daniela Bezdan, Nathaniel J. Szewczyk, Masafumi Muratani, Christopher E. Mason, Stefania Giacomello

Bibliographic record

VenueNature Communications · 2024
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsnot available
FundersNational Institute of Mental HealthFlorida State UniversityMinistry of Science and Higher Education of the Russian FederationAmes Research CenterNational Institutes of HealthNational Research Council CanadaSvenska Forskningsrådet FormasUniversity of NottinghamNational Aeronautics and Space AdministrationJapan Society for the Promotion of ScienceChildren's Hospital of PhiladelphiaGastro-Intestinal Research FoundationNuclear Safety and Security CommissionUK Research and Innovation
KeywordsSpace explorationSpaceflightHuman spaceflightSpace (punctuation)Data scienceHumanityScale (ratio)International Space StationFlourishingAtlas (anatomy)Computer scienceMedicineAerospace engineeringEngineeringPolitical sciencePsychologyGeography

Abstract

fetched live from OpenAlex

Future multi-year crewed planetary missions will motivate advances in aerospace nutrition and telehealth. On Earth, the Human Cell Atlas project aims to spatially map all cell types in the human body. Here, we propose that a parallel Human Cell Space Atlas could serve as an openly available, global resource for space life science research. As humanity becomes increasingly spacefaring, high-resolution omics on orbit could permit an advent of precision spaceflight healthcare. Alongside the scientific potential, we consider the complex ethical, cultural, and legal challenges intrinsic to the human space omics discipline, and how philosophical frameworks may benefit from international perspectives.

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)0.007
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.009
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.015
Scholarly communication0.0090.006
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.016
GPT teacher head0.360
Teacher spread0.344 · 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

Citations32
Published2024
Admission routes1
Has abstractyes

Explore more

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