MétaCan
Menu
Back to cohort
Record W2056891582 · doi:10.1097/jom.0000000000000323

A Meta-Analysis of Observational Studies of the Association Between Chronic Occupational Exposure to Lead and Amyotrophic Lateral Sclerosis

2014· review· en· W2056891582 on OpenAlexafffund
Mingdong Wang, James Gomes, Neil R. Cashman, Julian Little, Daniel Krewski

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2014
Typereview
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaPublic Health AgencyPublic Health Agency of CanadaUniversity of Ottawa
KeywordsAmyotrophic lateral sclerosisOdds ratioMedicineMeta-analysisConfidence intervalEpidemiologyObservational studyEnvironmental healthInternal medicineDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: The association between occupational exposure to lead and amyotrophic lateral sclerosis (ALS) was examined through systematic review and meta-analyses of relevant epidemiological studies and reported according to PRISMA guidelines. METHODS: Relevant studies were searched in multiple bibliographic databases through September 2013; additional articles were tracked through PubMed until submission. All records were screened in DistillerSR, and the data extracted from included articles were synthesized with meta-analysis. RESULTS: The risk of developing ALS among individuals with a history of exposure to lead was almost doubled (odds ratio, 1.81; 95% confidence interval, 1.39 to 2.36) on the basis of nine included case-control studies with specific lead exposure information, with no apparent heterogeneity across included studies (I = 14%). The attributable risk of ALS because of exposure to lead was estimated to be 5%. CONCLUSIONS: Previous exposure to lead may be a risk factor for ALS.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.280
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
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 head0.415
GPT teacher head0.423
Teacher spread0.008 · 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
GenreReview

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

Citations70
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Occupational and Environmental MedicineSame topicAmyotrophic Lateral Sclerosis ResearchFrench-language works237,207