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Record W2266752413 · doi:10.3138/cart.50.4.3126

Maps and the Meaning of the Cloud

2015· article· en· W2266752413 on OpenAlexvenueno aff
Michael P. Peterson

Bibliographic record

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2015
Typearticle
Languageen
FieldComputer Science
TopicData Management and Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsCloud computingWorkspaceNexus (standard)Meaning (existential)Computer scienceSymbol (formal)Scale (ratio)Data scienceGeographyCartographyArtificial intelligenceEpistemologyOperating system

Abstract

fetched live from OpenAlex

In its long history, cartography has always been at the forefront of adapting to new tools. The computer, first introduced 60 years ago, has represented perhaps the greatest change in how maps are made. The further combination of computers and communication technology changed how maps are distributed – and how they are used. Maps became more interactive and animated. The cloud, the nexus of computers and communication technology, is the most recent symbol of this change. While often simply defined as using the processing and storage capacity of data centres, the cloud is interpreted here as representing a workspace for the continued development of maps as a form of both analysis and communication. Examined are the development and formation of the cloud, the distribution of multi-scale pan-able (MSP) maps, and other related areas of cloud cartography.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.015
GPT teacher head0.258
Teacher spread0.244 · 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 designTheoretical or conceptual
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
Published2015
Admission routes1
Has abstractyes

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