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Record W6967612521 · doi:10.5281/zenodo.1160435

Open Lab Notebooks: An Extreme Open Science Initiative - Richard Akerman Presentation - Open Science In The Government Of Canada

2018· article· en· W6967612521 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsGovernment of Canada
Fundersnot available
KeywordsPresentation (obstetrics)Open scienceGovernment (linguistics)Open sourceOpen universityOpen government

Abstract

fetched live from OpenAlex

Richard Akerman's presentation for Structural Genomics Consortium (SGC) meeting "Open Lab Notebooks: An Extreme Open Science Initiative" http://www.thesgc.org/open-lab-notebooks-2018 January 19, 2018 in Ottawa, Ontario, Canada. Meeting supported by Canadian Institutes of Health Research (CIHR) and the Wellcome Trust. Twitter hashtag was #SGCOpenNotebooks Also on Slideshare https://www.slideshare.net/scilib/open-science-in-the-government-of-canada WebEx (audio plus slides) of presentation available at https://youtu.be/vxoxKVUWsUY?t=2h35m11s (my presentation starts at 2h35m11s). Due to technical difficulties the first three slides aren't displayed.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Open science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0120.014
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.067
GPT teacher head0.310
Teacher spread0.243 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2018
Admission routes2
Has abstractyes

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