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Record W3049736276 · doi:10.1051/itmconf/20203304001

Agile development of the SSH Open Marketplace: User Workshop

2020· article· en· W3049736276 on OpenAlexaff
Laure Barbot, Tracey Biller, Daan Broeder, Ron Dekker, Matej Ďurčo, Irene Vipavc, Marieke Willems

Bibliographic record

VenueITM Web of Conferences · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsCanarie
Fundersnot available
KeywordsPollingAgile software developmentContext (archaeology)Event (particle physics)World Wide WebOpen sourceComputer scienceOperating systemSoftware engineeringGeographySoftwarePhysics

Abstract

fetched live from OpenAlex

For the release of the Alpha version of the SSH Marketplace, we arranged a two-hour slot on 30 June 2020 during the ICTeSSH 2020 Conference. This report provides the context for the development of the Marketplace and presents the feedback received from testers who had been given prior access to the site, and from workshop attendees who were polled via Mentimeter during the event.

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)0.028
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.007

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 head0.274
GPT teacher head0.397
Teacher spread0.123 · 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 designQualitative
Domainnot available
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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