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Record W4235247528 · doi:10.1109/icse.2015.317

7th International Workshop on Modeling in Software Engineering (MiSE 2015)

2015· article· en· W4235247528 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

Venue2015 IEEE/ACM 37th IEEE International Conference on Software Engineering · 2015
Typearticle
Languageen
FieldComputer Science
TopicSoftware System Performance and Reliability
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSoftware engineeringComputer scienceCapability Maturity ModelKey (lock)Model-driven architectureSoftware developmentSoftwareMaturity (psychological)Systems engineeringEngineering managementEngineeringProgramming languageComputer security

Abstract

fetched live from OpenAlex

Models are an important tool in conquering the increasing complexity of modern software systems. Key industries are strategically directing their development environments towards more extensive use of modeling techniques. MiSE 2015 aimed to understand, through critical analysis, the current and future uses of models in the engineering of software-intensive systems. The MiSE workshop series has proven to be an effective forum for discussing modeling techniques from both the MDE and software engineering perspectives. An important goal of this workshop is to foster exchange between these two communities. In 2015 the focus was on considering the current state of tool support and the challenges that need to be addressed to improve the maturity of tools. There was also analysis of successful applications of modeling techniques in specific application domains, with attempts to determine how the participants' experiences can be carried over to other domains.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.001
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 head0.082
GPT teacher head0.310
Teacher spread0.228 · 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