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Record W6955070023 · doi:10.57757/iugg23-2514

The HAWC Satellite Mission: The Canadian Contribution to NASA AOS

2023· article· en· W6955070023 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePublication Database GFZ (GFZ German Research Centre for Geosciences) · 2023
Typearticle
Languageen
FieldComputer Science
TopicBig Data and Digital Economy
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWater vaporSatelliteNadirAerosolConstellationObservatoryAtmosphere (unit)Precipitation

Abstract

fetched live from OpenAlex

<!--!introduction!--><b></b> The HAWC (High-altitude Aerosols, Water vapour and Clouds) satellite mission is a highly synergistic observing system of three Canadian passive imaging sensors: the Aerosol Limb Imager (ALI) instrument, the Thin Ice Clouds in the Far InfraRed Emissions (TICFIRE), and the Spatial Heterodyne Observations of Water (SHOW) instrument.&nbsp; The mission was confirmed by the federal government as the Canadian contribution to NASA’s Atmospheric Observing System; a satellite constellation that will include multiple satellites with instruments to monitor aerosol, clouds, and precipitation as part of the Earth System Observatory (ESO).&nbsp; The HAWC instruments will work together to obtain vertically resolved measurements of aerosol and water vapour together with nadir measurements of radiation, thin ice cloud content, and cloud microphysical properties. These coordinated measurements will help build a more comprehensive understanding of climate-critical interactions of aerosol, cloud, and water vapour in the atmosphere.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0040.000
Scholarly communication0.0040.003
Open science0.0050.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.078
GPT teacher head0.355
Teacher spread0.277 · 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