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Record W2024362879 · doi:10.1038/bcj.2012.43

Extremely low-frequency magnetic fields and survival from childhood acute lymphoblastic leukemia: an international follow-up study

2012· article· en· W2024362879 on OpenAlexaffabout
Joachim Schüz, Kathrine Grell, Sally E. Kinsey, Martha S. Linet, MP Link, G. Mezei, B. B. Pollock, Eve Roman, Y Zhang, Mary L. McBride, Christoffer Johansen, Claudia Spix, Jun Hagihara, Akiko Saito, Jill Simpson, Leslie L. Robison, John D. Dockerty, Maria Feychting, Leeka Kheifets, Klaus Stensgaard Frederiksen

Bibliographic record

VenueBlood Cancer Journal · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectromagnetic Fields and Biological Effects
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersElectric Power Research InstituteKræftens Bekæmpelse
KeywordsHazard ratioMedicineConfidence intervalInternal medicineLymphoblastic LeukemiaSurvival analysisOverall survivalProportional hazards modelProspective cohort studySurvival rateLeukemia

Abstract

fetched live from OpenAlex

A previous US study reported poorer survival in children with acute lymphoblastic leukemia (ALL) exposed to extremely low-frequency magnetic fields (ELF-MF) above 0.3 μT, but based on small numbers. Data from 3073 cases of childhood ALL were pooled from prospective studies conducted in Canada, Denmark, Germany, Japan, UK and US to determine death or relapse up to 10 years from diagnosis. Adjusting for known prognostic factors, we calculated hazard ratios (HRs) and 95% confidence intervals (CI) for overall survival and event-free survival for ELF-MF exposure categories and by 0.1 μT increases. The HRs by 0.1 μT increases were 1.00 (CI, 0.93-1.07) for event-free survival analysis and 1.04 (CI, 0.97-1.11) for overall survival. ALL cases exposed to >0.3 μT did not have a poorer event-free survival (HR=0.76; CI, 0.44-1.33) or overall survival (HR=0.96; CI, 0.49-1.89). HRs varied little by subtype of ALL. In conclusion, ELF-MF exposure has no impact on the survival probability or risk of relapse in children with ALL.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.684

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)0.0000.000

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 head0.008
GPT teacher head0.248
Teacher spread0.239 · 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

Citations10
Published2012
Admission routes2
Has abstractyes

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