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Record W3170342330 · doi:10.5194/egusphere-egu21-13035

The HEMERA Balloon Research Infrastructure

2021· article· en· W3170342330 on OpenAlexaffabout
Felix Friedl-Vallon, P. Raizonville, André Vargas, Kristine Dannenberg, Marta Albano, Rainer Kirchhartz, Éric Vachon, Mattias Abrahamsson, Kjell Bøen, Xavier Dubois, Nathalie Huret, Neil Harris, P. Ubertini, Klaus Pfeilsticker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Energy Systems
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsStratosphereBalloonPhysicsAmpereInternational Space StationTroposphereEnvironmental scienceMeteorologyAstronomyCurrent (fluid)Medicine

Abstract

fetched live from OpenAlex

Stratospheric balloons are useful platforms for various research and technology needs. They allow to collect valuable data in many science fields, e.g. atmospheric science and astrophysics; they can be used for demonstrations in preparation of new space and Earth observation missions; they can be used to provide calibration/validation data for Earth observation space missions, or for dropping test objects from the stratosphere. Various types of balloons are available, corresponding to different missions: Zero Pressure Balloons (ZPB) for heavy payloads (100 kg to 3 tons) and short to medium duration (1 day to several days), Sounding Balloons (SB) for very light payloads (3 kg). Payloads can be flown at various altitudes between the ground surface up to 40 km, according the type of balloon and the kind of mission. Compared to satellites, stratospheric balloons can be operated at relatively low cost and with shorter lead times from the experiment idea to the flight. Mid-2017, a new Research Infrastructure called HEMERA has been selected by the European Commission within its programme Horizon 2020. The HEMERA objectives are to: Provide better and coordinated balloon access to the troposphere and stratosphere for scientific and technological research, in response to the scientific user needs. Attract new users to enlarge the community accessing the balloon infrastructure and foster scientific and technical collaboration. Enlarge the fields of science and technology research conducted with balloons. Improve the balloon service offered to scientific and technical users through innovative developments. Favour standardization, synergy, complementarities and industrialization through joint developments with greater cost-effectiveness. The project is coordinated by CNES and involves 13 partners in total, from various European entities and Canada. The project was kicked-off in late January 2018 and will be executed during 2018-2022. Six ZPB flights with a target payload mass of at least 150 kg are foreseen within HEMERA, offering free of charge access to users and scientists for various science measurements and/or for technology tests. In addition, several SB flights are foreseen. The launch sites will be Esrange in Sweden, Timmins in Canada, for the ZPB and Aire sur l'Adour in France for the SB. The selected experiments will fly on balloons during the years 2019-2022. Two Calls for Proposals were planned in the HEMERA project, the first was launched in 2018 and 39 answers from 12 countries have been received; 23 experiments have been selected. 31 answers have been received in the frame of the second call, from 10 countries. In total 39 experiments from 13 countries have been selected. The first HEMERA flights occurred in summer 2019 from Kiruna and Timmins. In addition, Open Access to balloon data will be organized in the frame of the Data Center, giving access to science data collected during the flights. Networking activities are planned in order to promote the Infrastructure in the European countries, and Joint Research activities are conducted in order to improve as far as possible the balloon offer in the view of the user needs.

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)0.005
metaresearch head score (Gemma)0.007
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.203
Threshold uncertainty score0.680

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0030.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2030.191

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 head0.013
GPT teacher head0.242
Teacher spread0.229 · 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
GenreOther

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

Citations1
Published2021
Admission routes2
Has abstractyes

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