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Record W2611615090 · doi:10.1002/cpe.4136

A reflection on the origins, evolution, and future of PRAGMA

2017· article· en· W2611615090 on OpenAlexfundno aff
Peter Arzberger

Bibliographic record

VenueConcurrency and Computation Practice and Experience · 2017
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsnot available
FundersCentro Nacional de Investigaciones CardiovascularesGlobal Lake Ecological Observatory NetworkNational Institute of Advanced Industrial Science and TechnologyNational Science Foundation
KeywordsReflection (computer programming)Context (archaeology)Set (abstract data type)Engineering ethicsCritical reflectionComputer scienceSociologyPolitical scienceData scienceEpistemologyEngineeringHistoryPedagogyPhilosophyArchaeology

Abstract

fetched live from OpenAlex

Summary All of the papers in this special collection have been shaped by and/or have helped shape PRAGMA. This paper, a reflection on PRAGMA, will provide additional technical, scientific, and human context to many of these papers. We hope to illustrate that it is the people who set directions by following their interests or posing questions, who make progress by honoring their commitments and who build community by establishing open communications and trust.

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)0.049
metaresearch head score (Gemma)0.072
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: Commentary
Teacher disagreement score0.049
Threshold uncertainty score0.258

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.072
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.042
Scholarly communication0.0200.047
Open science0.0040.010
Research integrity0.0070.028
Insufficient payload (model declined to judge)0.0070.002

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 head0.048
GPT teacher head0.353
Teacher spread0.305 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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