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Record W4386911017

Current Methods for Hyperpolarized [1-<sup>13</sup>C]pyruvate MRI Human Studies.

2023· preprint· en· W4386911017 on OpenAlexaff
Peder E.Z. Larson, Jenna Bernard, James A. Bankson, Nikolaj Bøgh, Robert Bok, Albert P. Chen, Charles H. Cunningham, Jeremy W. Gordon, Jan‐Bernd Hövener, Christoffer Laustsen, Dirk Mayer, Mary A. McLean, Franz Schilling, James Slater, Jean‐Luc Vanderheyden, Cornelius von Morze, Daniel B. Vigneron, Duan Xu

Bibliographic record

VenuePubMed · 2023
Typepreprint
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institutes of HealthNational Cancer InstituteChang Gung Medical FoundationEidgenössische Technische Hochschule ZürichAlbert-Ludwigs-Universität FreiburgUniversity of Texas MD Anderson Cancer CenterMemorial Sloan-Kettering Cancer CenterInstitute for Bioengineering of CataloniaUniversity of OxfordDanmarks Tekniske UniversitetAarhus UniversitetTechnische Universität München
KeywordsMedicineComputer scienceNeuroscienceMedical physicsBiology
DOInot available

Abstract

fetched live from OpenAlex

C MRI Consensus Group" as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods & Equipment study groups. It further aims to provide a comprehensive reference for future consensus building as the field continues to advance human studies with this metabolic imaging modality.

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 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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.046
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0460.059

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 head0.159
GPT teacher head0.439
Teacher spread0.279 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations4
Published2023
Admission routes1
Has abstractyes

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