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Record W2158366533 · doi:10.1109/icgse.2006.261226

MasePlanner: A Card-Based Distributed Planning Tool for Agile Teams

2006· article· en· W2158366533 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAgile software developmentWorkspacePlan (archaeology)Computer scienceAgile Unified ProcessHuman–computer interactionSoftware engineeringProcess managementEngineeringRobotArtificial intelligenceOperating systemSoftwareSoftware developmentGeography

Abstract

fetched live from OpenAlex

Supporting agile teams from afar as they plan projects is a challenge. In this paper, we present a planning tool, MasePlanner, which supports agile teams as they collaborate in a distributed environment during their planning meetings. Combined with an audio link, our tool supports natural interaction similar to those found in collocated agile planning environments. MasePlanner supports planning in both vertical and horizontal tabletop workspaces by allowing participants to use interaction techniques such as moving and piling of story cards. By implementing a strong index-card metaphor, the tool aims to be more closely aligned with natural environments

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.862
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.018
GPT teacher head0.254
Teacher spread0.236 · 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

Quick stats

Citations20
Published2006
Admission routes1
Has abstractyes

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