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Record W150751362 · doi:10.11575/prism/28781

Geomatics and the New Cyber-infrastructure

2008· article· en· W150751362 on OpenAlexafffund
J. A. R. Blais, Harold Esche

Bibliographic record

VenuePRISM (University of Calgary) · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Resources CanadaU.S. Department of Homeland Security
KeywordsGeomaticsGeographyCartographyRegional scienceData scienceComputer science

Abstract

fetched live from OpenAlex

Geomatics is a very active field of applied science and engineering which deals with multi-resolution geospatial and spatio-temporal information for all kinds of scientific, engineering and administrative appli cations.Rapidly changing communication and High Performance Computing (HPC) technologies have brought about fundamental changes in the handling of geospatial and related information.As a result, new specialized knowledge and expertise are expected and refined in the workplace.Cyber-infrastructure refers to the new virtual environments in which advanced data processing and management services are accessi ble through high-performance communication networks, primarily for collaborative research, development and instructional purposes.These new trends are very likely to transform the community by bringing scien tists, researchers, students and practitioners to share the same data, tools, procedures and expertise when dealing with geospatial and related information.Such exciting possibilities as virtual observatories and J.A. Rod Blais workplaces are discussed, with examples to illustrate some of the far-reaching implications for not only blais@ucalgary.causers in Geomatics, but society in general.La géomatique est un domaine très actif des sciences appliquées et du génie qui s'occupe de l'information géospatiale et spatio-temporelle à multi-résolution pour divers genres d'applications scientifiques, de génie et administratives.Les communications en évolution rapide et les technologies High Performance Computing (HPC) (à haut débit) ont entraîné des changements fondamentaux dans la manipulation de l'information géospatiale et l'information connexe.Ainsi, de nouvelles connaissances et expertise spécialisées sont attendues et raffinées dans le milieu de travail.La cyber-infrastructure fait référence aux nouveaux environnements virtuels dans lesquels les services de traitement et de gestion avancés de données sont accessibles par l'en tremise de réseaux de communications à rendement élevé, surtout pour des fins de recherche, de développe ment et de formation en collaboration.Il est très probable que les nouvelles tendances transformeront la Harold Esche collectivité en permettant aux scientifiques, chercheurs, étudiants et praticiens de partager les mêmes données, esche@ucalgary.caoutils, procédures et expertise en travaillant avec les renseignements géospatiaux et l'information connexe.On discute des possibilités excitantes comme des observatoires et milieux de travail virtuels et on donne des exemples pour illustrer certaines répercussions de grande portée non seulement pour les utilisateurs du domaine de la géomatique, mais pour la société dans son ensemble.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.015
Scholarly communication0.0080.015
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.009
GPT teacher head0.155
Teacher spread0.147 · 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
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

Citations11
Published2008
Admission routes2
Has abstractyes

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