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Record W2774333412 · doi:10.1139/apnm-2017-0653

Trace lithium in Texas tap water is negatively associated with all-cause mortality and premature death

2017· article· en· W2774333412 on OpenAlexafffundvenue
Val A. Fajardo, Paul J. LeBlanc, Val Andrei Fajardo

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2017
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsBrock UniversityUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCenters for Disease Control and PreventionInternational Business Machines Corporation
KeywordsTap waterLithium (medication)Environmental healthEnvironmental scienceMedicineEnvironmental engineeringInternal medicine

Abstract

fetched live from OpenAlex

Lithium in tap water was previously found to have life-extending effects across 18 Japanese municipalities. Using a larger dataset with several Texas counties, our study shows that lithium concentrations in tap water are negatively associated with all-cause mortality (r = -0.18, p = 0.006, 232 counties) and years of potential life lost (r = -0.22, p = 0.001, 214 counties). Thus, our present findings extend and reinforce lithium's purported life-prolonging effect in humans.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.076
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.296
Teacher spread0.261 · 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 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

Citations25
Published2017
Admission routes3
Has abstractyes

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