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Record W2981733425 · doi:10.3389/fphys.2019.01332

Corrigendum: Blood Flow Restriction Exercise: Considerations of Methodology, Application, and Safety

2019· erratum· en· W2981733425 on OpenAlexaff
Stephen D. Patterson, Luke Hughes, Stuart A. Warmington, Jamie F. Burr, Brendan R. Scott, Johnny G. Owens, Takashi Abe, Jakob Lindberg Nielsen, Cleiton Augusto Libardi, Gilberto Laurentino, Gabriel Rodrigues Neto, Christopher R. Brandner, Juan Martín‐Hernández, Jeremy P. Loenneke

Bibliographic record

VenueFrontiers in Physiology · 2019
Typeerratum
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBlood flow restrictionComputer scienceBlood flowMedicineCardiologyInternal medicineResistance training

Abstract

fetched live from OpenAlex

In the published article, there was an error regarding the affiliation for Johnny Owens. His affiliation is reported as Owens Recovery Science. We would like to add that this is a private company who run educational courses on the topic area. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated

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)0.008
metaresearch head score (Gemma)0.124
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.124
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0490.059

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 head0.023
GPT teacher head0.270
Teacher spread0.247 · 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
GenreOther

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

Citations37
Published2019
Admission routes1
Has abstractyes

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