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Record W4386736479 · doi:10.21606/drs.2022.913

Editorial: DRS2022 Labs

2022· editorial· en· W4386736479 on OpenAlexaff
Juan Sádaba

Bibliographic record

VenueProceedings of DRS · 2022
Typeeditorial
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsKey (lock)Living labCultural heritageLibrary sciencePolitical scienceEngineeringEngineering ethicsEngineering managementSociologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The Bilbao Labs initiative emerged from the conference, aiming to address design challenges specific to Bilbao and the surrounding region. Four key challenges were identified: Urban Habitat, Digital Ecosystems, Cultural Heritage, and Creative Industries and Public Space. The Labs involved local and international research teams, fostering collaboration and continuous interaction before, during, and after the conference. Five international Lab proposals, along with local institutions, contributed to the success of the Bilbao-based DRS conference Labs, reflecting the growing importance of design research in addressing complex challenge.

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)0.006
metaresearch head score (Gemma)0.024
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.024
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.002
Science and technology studies0.0050.003
Scholarly communication0.0090.005
Open science0.0040.002
Research integrity0.0230.021
Insufficient payload (model declined to judge)0.0290.029

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 head0.009
GPT teacher head0.224
Teacher spread0.214 · 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
GenreEditorial

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
Published2022
Admission routes1
Has abstractyes

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