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Record W2985227638 · doi:10.1109/igarss.2019.8897898

Canadian Water Microsatellite Mission - Concept Design

2019· article· en· W2985227638 on OpenAlexaffabout
Kiana Zolfaghari, Marie Hoekstra, Claude Duguay, David Rudolph, Ian D’Souza

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsHoneywell (Canada)University of Waterloo
Fundersnot available
KeywordsFutures contractWater qualityWater resourcesEnvironmental scienceEnvironmental resource managementWater supplyEcosystemRange (aeronautics)Water cycleComputer scienceRemote sensingWater resource managementBusinessGeographyEngineeringEcologyEnvironmental engineering

Abstract

fetched live from OpenAlex

Canada has vast water resources that span an enormous range in geography, climate, and ecosystems [1]. Water supply and water quality are the two critical issues relevant to water resources, not only in Canada but globally in a warming climate. The water microsatellite mission described here aims to better prepare end users to respond to the emerging spectrum of water futures issues by revolutionizing remote sensing of water quality and quantity parameters, and permitting unprecedented interconnection and data gathering from Canadian environmental monitoring networks.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.015
GPT teacher head0.194
Teacher spread0.179 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations0
Published2019
Admission routes2
Has abstractyes

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