MétaCan
Menu
← Back to cohort
Record W6931361688 · doi:10.5281/zenodo.3825074

Balloon astrophysics in Canada over the next decade

2019· article· en· W6931361688 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsHerzberg Institute of AstrophysicsUniversity of British ColumbiaMcGill UniversityQueen's University
Fundersnot available
KeywordsBalloonWhite paperSpace explorationInfrared astronomyGraduate studentsKey (lock)Service (business)

Abstract

fetched live from OpenAlex

Stratospheric balloons offer near space observing conditions for a small fraction of the cost of an equivalent satellite. Balloon telescopes can make cutting-edge astrophysical observations, while also providing a platform to advance the technology readiness level of key systems for future space missions. Furthermore, balloon astronomy offers outstanding training opportunities. Typical experiment timeframes allow graduate students to play a key role in the instrument design, field campaigns, and scientific data analysis. In this white paper we will overview Canadian involvement in balloon astrophysics and outline the priorities of the balloon astronomy community for the coming decade. These priorities are: continued stable funding for the development of balloon-borne experiments, competitions for larger funding awards that would support the building of balloon-borne observatories or equivalent particle astrophysics experiments, support for PIs to access existing pointing platforms and balloon gondola technology, and opportunities for long duration conventional balloon and super-pressure balloon flights.

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)0.003
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.089
Threshold uncertainty score0.644

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0060.002
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0330.005

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 head0.049
GPT teacher head0.270
Teacher spread0.221 · 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

Citations0
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicNeuroscience and Neuropharmacology Research→French-language works237,207→