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Record W2197599172 · doi:10.5589/q11-006

ExoGIS: An internet-based geographic information system in support of planetary science

2011· article· en· W2197599172 on OpenAlexaffvenueabout
Mickaël Germain, M. Phaneuf, G.B. Bénié, M -C Williamson, V. Hipkin

Bibliographic record

VenueCanadian aeronautics and space journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaUniversité de SherbrookeCanadian Space Agency
Fundersnot available
KeywordsGeospatial analysisMars Exploration ProgramThe InternetGeographic information systemField (mathematics)Computer scienceEngineeringGeographyEarth scienceSystems engineeringWorld Wide WebRemote sensingAstrobiologyGeology

Abstract

fetched live from OpenAlex

The Canadian Space Agency (CSA) actively supports research projects in the field of planetary sciences that are carried out through the Canadian Analogue Research Network (CARN). CARNd projects provide the background data used in comparative studies of the Earth, Moon, and Mars. These studies require sophisticated tools for the visualization, manipulation, analysis, and interpretation of geospatial terrestrial and planetary databases. The large amount of data, gathered through current and future missions, must be managed for easy access by principal investigators, CSA staff, and stakeholders from government, universities, industry, and other space agencies. We are currently developing an internet-based geographic information system (WebGIS) that has three objectives: (i) to promote and facilitate research at analogue sites in Canada and other locations where CSA field deployments are carried out; (ii) to forge stronger links with the international Earth and planetary science community by sharing geospatial information; and (iii) to give visibility to the CSA in the field of analogue and planetary GIS. We propose building a WebGIS architecture according to the international standards developed by the Open Geospatial Consortium for terrestrial data, and the International Planetary Data Alliance for planetary bodies. To illustrate the versatility of WebGIS applications, we use an example based on the composition of lunar rocks produced from datasets acquired by Lunar Prospector and extracted from the Planetary Data System.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.231
Teacher spread0.205 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2011
Admission routes3
Has abstractyes

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