MétaCan
Menu
Back to cohort
Record W2896246835 · doi:10.1109/ms.2018.2874323

Toward Solving Social and Technical Problems in Open Source Software Ecosystems: Using Cause-and-Effect Analysis to Disentangle the Causes of Complex Problems

2018· article· en· W2896246835 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

VenueIEEE Software · 2018
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsPolytechnique MontréalUniversité Laval
FundersFonds De La Recherche Scientifique - FNRS
KeywordsOpen source softwareKey (lock)SoftwareSoftware developmentSocial software engineeringSoftware peer reviewComputer scienceOpen sourceSoftware engineeringSoftware analyticsScale (ratio)Knowledge managementData scienceBusinessProcess managementSoftware development processSoftware constructionComputer securityOperating system

Abstract

fetched live from OpenAlex

Many open source software (OSS) products today are market leaders, 1 which suggests that the development of OSS is key to the growth of the software industry. OSS projects increasingly tend to be incorporated in large-scale projects or "software ecosystems" to reduce effort and accelerate innovation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.496
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.002
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 head0.081
GPT teacher head0.331
Teacher spread0.249 · 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