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Record W1597278287 · doi:10.1002/pbc.25962

Corrigendum: The Associations Between Maternal Factors During Pregnancy and the Risk of Childhood Acute Lymphoblastic Leukemia: A Meta-Analysis

2016· erratum· en· W1597278287 on OpenAlexaff
Kangkang Yan, Xuejing Xu, Xiaodong Liu, Xikui Wang, Shucheng Hua, Chunpeng Wang, Xin Liu

Bibliographic record

VenuePediatric Blood & Cancer · 2016
Typeerratum
Languageen
FieldImmunology and Microbiology
TopicT-cell and Retrovirus Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineMeta-analysisPregnancyLymphoblastic LeukemiaConfidence intervalBlood cancerChildhood cancerLeukemiaRisk factorChildhood leukemiaOncologyPediatricsObstetricsCancerInternal medicineGenetics

Abstract

fetched live from OpenAlex

Because of the erroneous application of multiple publications, the conclusions of our recent paper (Pediatr Blood Cancer 2015;62:1162-70) were not reliable. The corrected results show that coffee drinking during pregnancy was risk factor for childhood acute lymphoblastic leukemia (OR = 1.44, 95% confidence interval = 1.07-1.92).

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)0.010
metaresearch head score (Gemma)0.098
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.098
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0290.007

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 head0.017
GPT teacher head0.230
Teacher spread0.214 · 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 designMeta-analysis
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

Citations23
Published2016
Admission routes1
Has abstractyes

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