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Record W4365455420 · doi:10.31219/osf.io/xm5jn

Promoting Open-Science and Accessible Student Training: The Open-Science fabrication laboratory model

2023· preprint· en· W4365455420 on OpenAlexaffabout
Maxime Bleau, Ismaël Djerourou

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsComputer scienceMultitudeOpen scienceEngineering managementKnowledge managementEngineering ethicsEngineeringPolitical science

Abstract

fetched live from OpenAlex

The Open-Science fabrication laboratory movement is an ongoing student initiative at the School of Optometry of the University of Montreal. The pilot project, the OptoFAB, is a collaborative space specially dedicated to producing low-cost material for research purposes based on the Open-Science and Maker movements. It aims to:1.Promote Open-Science and the fast dissemination and replication of research.2.Provide accessible training for students in a multitude of disciplines (i.e., 3D printing, 3D modeling, coding, robotics).3.Encourage interdisciplinary collaborations between the different programs (e.g., research, clinical, engineering).Our laboratory model will benefit laboratories and provide students with more opportunities during and beyond their (under)graduate studies. As students are the next generation of researchers, the Open-Science fabrication laboratory aims to give them more resources to develop multi-faceted skills, improve their self-efficacy and help them build their research careers. This paper describes our model and how we aim to measure our impact ongoingly and to improve the tools and services we put at students’ disposition. We hope that, through this paper, other universities might join the movement and replicate our model within their research programs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0060.006
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.345
Teacher spread0.263 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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
Published2023
Admission routes2
Has abstractyes

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