ArticleAstrobiology2019
Developing Future Deep-Space Telecommunication Architectures: A Historical Look at the Benefits of Analog Research on the Development of Solar System Internetworking for Future Human Spaceflight.
Article in Astrobiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- SANS-CNN: An automated machine learning technique for spaceflight associated neuro-ocular syndrome with astronaut imaging data.NPJ microgravity · 2024Article
- Causal diagramming for assessing human system risk in spaceflight.NPJ microgravity · 2024Review
- Estimating medical risk in human spaceflight.NPJ microgravity · 2022Article
- Using Science-Driven Analog Research to Investigate Extravehicular Activity Science Operations Concepts and Capabilities for Human Planetary Exploration.Astrobiology · 2019Article
- Assessing the Acceptability of Science Operations Concepts and the Level of Mission Enhancement of Capabilities for Human Mars Exploration Extravehicular Activity.Astrobiology · 2019Article
- The BASALT Research Program: Designing and Developing Mission Elements in Support of Human Scientific Exploration of Mars.Astrobiology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Exploration analog field tests, missions, and deployments enable the integration and validation of new and experimental concepts and/or technologies through strategic experimental design. The results of these operations often create new capabilities for exploration and increase confidence in, and credibility of, emerging technologies, usually at very low cost and risk to the test subjects involved. While these experiments resemble missions 10-30 years into the future, insights obtained are often of immediate value. Knowledge gained in the field translates into strategic planning data to assist long-range exploration planners, and planners influence the experimental design of field deployments, creating a synergistic relationship. The Biologic Analog Science Associated with Lava Terrains (BASALT) communication architecture is a high-fidelity analog program that emulates conditions impacting future explorers on the martian surface. This article provides (1) a brief historical review of past analog operations that deliberately used elements of a flight-like telecommunication infrastructure to add fidelity to the test, (2) samples of the accomplishments made through analog operations, and (3) potentially significant deep-space telecommunication insights gained from the BASALT program in support of future extravehicular activity exploration of Mars. This article is paired with and complements Miller et al. in this issue which focuses on the telecommunication infrastructure utilized by the BASALT team during the field deployment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.