MétaCan
Menu
← Back to cohort
Record W2517252232 · doi:10.1080/13662716.2016.1240068

The open innovation research landscape: established perspectives and emerging themes across different levels of analysis

2016· article· en· W2517252232 on OpenAlexaff
Marcel Bogers, Ann‐Kristin Zobel, Allan Afuah, Esteve Almirall, Sabine Brunswicker, Linus Dahlander, Lars Frederiksen, Annabelle Gawer, Marc Gruber, Stefan Haefliger, John Hagedoorn, Dennis Hilgers, Keld Laursen, Mats Magnusson, Ann Majchrzak, Ian P. McCarthy, Kathrin M. Moeslein, Satish Nambisan, Frank T. Piller, Agnieszka Radziwon, Cristina Rossi‐Lamastra, Jonathan Sims, Anne L. J. Ter Wal

Bibliographic record

VenueIndustry and Innovation · 2016
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEconomic geographyOpen innovationGeographyRegional scienceBusinessMarketing

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.071
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.929
Threshold uncertainty score0.376

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0710.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0250.027
Science and technology studies0.0110.056
Scholarly communication0.0420.052
Open science0.0040.021
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0040.000

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 head0.108
GPT teacher head0.406
Teacher spread0.298 · 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.

Study designTheoretical or conceptual
DomainMethods
GenreReview

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

Citations956
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueIndustry and Innovation→Same topicOpen Source Software Innovations→French-language works237,207→