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Record W2610687538

On the Suitability of Mobile Cloud Computing at the Tactical Edge

2014· article· en· W2610687538 on OpenAlexaboutno aff
Mazda Salmanian, David Brown, K. Perrett, Darcy Simmelink, Tricia Wilink, Phil Vigneron, Li Li, Francois St Onge, Dang Quan Nguyen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOpportunistic and Delay-Tolerant Networks
Canadian institutionsnot available
Fundersnot available
KeywordsCloud computingSituation awarenessCommand and controlComputer securityComputer scienceControl (management)Information OperationsEngineeringTelecommunicationsOperating system
DOInot available

Abstract

fetched live from OpenAlex

Abstract : On 21 May 2013, DGSTJFD requested advice from the Canadian National Lead of The Technical Cooperation Panel (TTCP) Command, Control, Communications and Intelligence(C3I) Action Group 2 (AG2) on Cloud Computing regarding how cloud computing could be used in a tactical environment to garner important Command and Control (C2) and situational awareness information. In response to this request, and based on the recommendations from an AG2 Technical Report on coalition cloud computing, scientists in the Cyber Operations and Signals Warfare (COSW) Section of Defence Research and Development Canada (DRDC)contracted a preliminary study to assess the use of tactical clouds in enhancing warfighter effectiveness. The study produced a number of diverse use-cases, architectures, and scenarios for tactical cloud computing.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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