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Record W4393891535 · doi:10.5281/zenodo.3975887

ISMRM Reproducible Research Study Group: Data for the paper "CG-SENSE revisited: Results from the first ISMRM reproducibility challenge"

2020· dataset· en· W4393891535 on OpenAlexaff
Oliver Maier, Steven H. Baete, Alexander Fyrdahl, Kerstin Hammernik, Seb Harrevelt, Lars Kasper, Agâh Karakuzu, Michael Loecher, Franz Patzig, Ye Tian, Ke Wang, Daniel Gallichan, Martin Uecker, Florian Knöll

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typedataset
Languageen
FieldMaterials Science
TopicMachine Learning in Materials Science
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsReproducibilityGroup (periodic table)Computer scienceStatisticsChemistryMathematics

Abstract

fetched live from OpenAlex

Challange data (brain/heart) and supplementary data (cardiac/rawdata_sprial) for the paper "CG-SENSE revisited: Results from the first ISMRM reproducibility 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 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)0.058
metaresearch head score (Gemma)0.091
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0580.091
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0110.001
Scholarly communication0.0050.001
Open science0.0150.021
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0120.018

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 head0.135
GPT teacher head0.335
Teacher spread0.200 · 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
GenreDataset

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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