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Record W1831038545

Tailoring software process capability/maturity models for telemedicine systems

2012· article· en· W1831038545 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

VenueAmericas Conference on Information Systems · 2012
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsSoftware qualityComputer scienceCapability Maturity ModelSoftware quality controlQuality (philosophy)LeanCMMIProcess (computing)Software development processSoftware engineeringSoftware quality analystSoftware developmentSoftwareSystems engineeringReliability engineeringEngineeringOperating system
DOInot available

Abstract

fetched live from OpenAlex

Developing high-quality asynchronous store-and-forward telemedicine systems (ASFTSs) remains a challenge. However, there is no accepted understanding as to what are the important quality characteristics for this type of software system and/or what defines a mature software process for producing high-quality ASTFSs. Through adopting a multi-step research methodology, we define a quality model for ASFTSs indicating relevant quality characteristics and their priority for this specific type of software system based upon ISO/IEC 25010. We, then, propose an extended software process capability/maturity model based on ISO/IEC 15504 and ISO/IEC 12207 to meet these particular quality requirements. The resulting model can be used to both guide the development and the evaluation of such systems. We expect that the availability of such a customized model will facilitate the development of high-quality ASFTSs, reducing related risks and improving the quality of telemedicine services.

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)0.001
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 score0.978
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.005
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 head0.035
GPT teacher head0.280
Teacher spread0.245 · 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