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Record W3195450812 · doi:10.1145/3474351

Finding the art in systems conversions, naming

2021· article· en· W3195450812 on OpenAlexaff
Doug Meil, Mario Antoine Aoun

Bibliographic record

VenueCommunications of the ACM · 2021
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsDozenComputer scienceWorld Wide WebPublicationAdvertisingBusinessMathematics

Abstract

fetched live from OpenAlex

The Communications website, http://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of Communications , we'll publish selected posts or excerpts. twitter Follow us on Twitter at http://twitter.com/blogCACM http://cacm.acm.org/blogs/blog-cacm Doug Meil considers a third distinct type of development, while Mario Antoine Aoun ponders alternate names for ACM.

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)0.011
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0080.019
Scholarly communication0.0200.035
Open science0.0020.008
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0350.013

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 head0.056
GPT teacher head0.305
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

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 designNot applicable
Domainnot available
GenreCommentary

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
Published2021
Admission routes1
Has abstractyes

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