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Record W1554067319

El uso de Internet con software libre y fuentes espaciales abiertas para colaborar en la toma de decisiones

2008· article· es· W1554067319 on OpenAlexaboutno aff
Geoff Hall, Juan Pablo Alperín, Santiago Kerrigan

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2008
Typearticle
Languagees
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyArt
DOInot available

Abstract

fetched live from OpenAlex

En los ultimos anos ha habido un gran crecimiento del potencial de las tecnologias “open source” (codigo abierto). En el 2005, la comunidad de codigo abierto geoespacial se consolida como una organizacion sin fines de lucro llamada la Open Geospatial Foundation (OSGeo). Colectivamente estos eventos han preparado el terreno para una epoca importante en el desarrollo de herramientas para aplicaciones geoespaciales. Este articulo describe el desarrollo de una herramienta que se origino a partir de estos eventos y fue desarrollada en la Universidad de Waterloo, Canada, durante los ultimos cuatro anos.

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)0.010
metaresearch head score (Gemma)0.028
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 score0.070
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.014
Science and technology studies0.0050.004
Scholarly communication0.0130.014
Open science0.0020.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.003

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 head0.014
GPT teacher head0.281
Teacher spread0.267 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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