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Record W2742011265 · doi:10.1038/gim.2017.107

Patient care standards for primary mitochondrial disease: a consensus statement from the Mitochondrial Medicine Society

2017· review· en· W2742011265 on OpenAlexaff
Sumit Parikh, Amy Goldstein, Amel Karaa, Mary Kay Koenig, Irina Anselm, Catherine Brunel‐Guitton, John Christodoulou, Bruce H. Cohen, David Dimmock, Gregory M. Enns, Marni J. Falk, Annette Feigenbaum, Richard E. Frye, Jaya Ganesh, David A. Griesemer, Richard Haas, Rita Horváth, Mark Korson, Michael C. Kruer, Michelangelo Mancuso, Shana E. McCormack, Marie Josée Raboisson, Tyler Reimschisel, Ramona Salvarinova, Russell P. Saneto, Fernando Scaglia, John M. Shoffner, Peter W. Stacpoole, Carolyn M. Sue, Mark A. Tarnopolsky, Clara van Karnebeek, Lynne A. Wolfe, Zarazuela Zolkipli Cunningham, Shamima Rahman, Patrick F. Chinnery

Bibliographic record

VenueGenetics in Medicine · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsMcMaster UniversityCentre Hospitalier Universitaire Sainte-JustineBC Children's HospitalSickKids FoundationUniversity of TorontoUniversity of British ColumbiaHospital for Sick ChildrenUniversité de Montréal
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesWellcome Trust Centre for Mitochondrial ResearchMedical Research CouncilNewcastle UniversityNational Institute for Health and Care ResearchWellcome Trust
KeywordsStatement (logic)Delphi methodPrimary careConsensus conferenceMedicineFamily medicineMEDLINEAlternative medicinePathologyPolitical scienceLawInternal medicineComputer science

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.022
metaresearch head score (Gemma)0.025
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: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0050.004
Research integrity0.0090.011
Insufficient payload (model declined to judge)0.0040.002

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 head0.056
GPT teacher head0.376
Teacher spread0.320 · 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
GenreReview

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

Citations295
Published2017
Admission routes1
Has abstractno

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