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Record W2024678590 · doi:10.1145/602421.602453

Use of the SAND spatial browser for digital government applications

2003· article· en· W2024678590 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.

Bibliographic record

VenueCommunications of the ACM · 2003
Typearticle
Languageen
FieldComputer Science
TopicData Management and Algorithms
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceInterface (matter)Spatial analysisWorld Wide WebThe InternetInformation retrievalWeb browserSpatial data infrastructureAgency (philosophy)Remote sensingGeography

Abstract

fetched live from OpenAlex

Numerous federal agencies produce official statistics made accessible to ordinary citizens for searching and data retrieval. This is frequently done via the Internet through a Web browser interface. If this data is presented in textual format, it can often be searched and retrieved by such attributes as topic, responsible agency, keywords, or press release. However, if the data is of spatial nature, for example, in the form of a map, then using text-based queries is often too cumbersome for the intended audience. We describe the use of the SAND Spatial Browser to provide more power to users of these databases by enabling them to define and explore the specific spatial region of interest graphically. The SAND Spatial Browser allows users to form either purely spatial or mixed spatial/nonspatial queries intuitively, which can present information to users that might have been missed if only a textual interface was available.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0200.012
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 head0.061
GPT teacher head0.266
Teacher spread0.204 · 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