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Record W2998428611 · doi:10.15173/m.v1i36.2334

Pyruvate Kinase Deficiency and Developments In its Treatment

2019· article· en· W2998428611 on OpenAlexvenueno aff
The Meducator, Kashyap Patel, Omaike Sikder, Nikhil Hariharan, Jeff Zhang

Bibliographic record

VenueThe Meducator · 2019
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsnot available
Fundersnot available
KeywordsPyruvate kinaseMedicineInternal medicineGlycolysis

Abstract

fetched live from OpenAlex

Pyruvate kinase (PK) is an enzyme involved in ATP production in the glycolytic pathway. PK deficiency is a rare, autosomal recessive disorder that manifests with hemolytic anemia of variable severity, partly due to an insufficiency of ATP production in erythrocytes. Its exact prevalence is unknown due to lack of awareness and challenges in making the diagnosis of PK deficiency. Current treatments for PK deficiency include blood transfusion and splenectomy, which focus on temporarily alleviating anemia and reducing hemolysis, respectively. Due to the rarity of this condition and its variable severity, a systematic treatment protocol for novel therapies is difficult to compile and validate. Oral administration of mitapivat, an allosteric activator of erythrocyte PK, is a novel treatment. Despite its promising effects on the hemoglobin levels in PK deficient patients, mitapivat’s efficacy and safety profiles must be determined through randomized controlled trials.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.024
GPT teacher head0.278
Teacher spread0.255 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2019
Admission routes1
Has abstractyes

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