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Record W6890112853 · doi:10.34734/fzj-2024-04506

The Utopian Model: How The Neuro Has Become An Open Science Institution

2020· article· en· W6890112853 on OpenAlexaboutno aff

Bibliographic record

VenueJuSER Publikationsportal · 2020
Typearticle
Languageen
FieldNeuroscience
TopicUndergraduate Neuroscience Education and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOpen scienceInstitutionAllianceCitizen scienceOfficer

Abstract

fetched live from OpenAlex

Episode Summary: In this episode we talk to Dylan Roskams-Edris from Open Science Alliance Officer at Tanenbaum Open Science Institute and The Neuro in Canada. We discussed how The Neuro made itself into the worlds first open neuroscience institution, the challenges and opportunities of embracing Open Science at an institutional level, how Open Science itself needs to be more open, and the potential for scientists working in such a system. Episode Links: Dylan Roskams-Edris Twitter The Neuro Twitter

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.768
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0060.003
Scholarly communication0.0070.005
Open science0.0050.001
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 head0.259
GPT teacher head0.371
Teacher spread0.111 · 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 designTheoretical or conceptual
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

Citations0
Published2020
Admission routes1
Has abstractyes

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