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Record W2593685779 · doi:10.1194/jlr.m072207

Lipid and lipoprotein abnormalities in acute lymphoblastic leukemia survivors

2017· article· en· W2593685779 on OpenAlexafffund
Sophia Morel, J.L. Leahy, Maryse Fournier, Benoı̂t Lamarche, Carole Garofalo, Guy Grimard, Floriane Poulain, Edgard Delvin, Caroline Laverdière, Maja Krajinović, Simon Drouin, Daniel Sinnett, Valérie Marcil, Émile Lévy

Bibliographic record

VenueJournal of Lipid Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversité LavalUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersInstitute of Cancer ResearchGarron Family Cancer CentreFonds de Recherche du Québec - SantéCancer Research SocietyCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsDyslipidemiaInternal medicineEndocrinologyVery low-density lipoproteinApolipoprotein BCholesterolLipoproteinLipid profileMedicineTriglycerideChemistryObesity

Abstract

fetched live from OpenAlex

Acute lymphoblastic leukemia (ALL) accounts for 25% of all childhood malignancies and represents the most common form of leukemia in children. Cure rates for ALL now exceed 85%, allowing a growing number of childhood survivors to live into adulthood (1). However, survivors face severe, even life-threatening, long-term sequelae decades after the end of treatments (2, 3). Of interest, ALL survivors are at increased risk of developing cardiovascular conditions, including congestive heart failure, coronary artery disease, myocardial infarction, cardiac arrest, and cerebrovascular accidents (4-6). Studies on pediatric ALL survivors have reported a high prevalence of the typical components of the metabolic syndrome (MetS), such as obesity (7), hypertension (8), glucose tolerance (9), or dyslipidemia (10), and clustering of the three surrogates of MetS was also described (11). While chemo-and radiotherapy have often been associated with the development of these disorders in childhood cancer survivors (12-15), the precise etiology and the mechanisms of these late complications are not fully understood.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.335
Teacher spread0.306 · 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 designNot applicable
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

Citations68
Published2017
Admission routes2
Has abstractyes

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