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Record W3096837140 · doi:10.3390/app10217489

Air Pollution Associates with Cancer Incidences in Poland

2020· article· en· W3096837140 on OpenAlexaboutno aff
Norbert Tuśnio, Jakub Fichna, Przemysław Nowakowski, Piotr Tofiło

Bibliographic record

VenueApplied Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPollutantEnvironmental healthAir pollutionPopulationEnvironmental sciencePollutionLung cancerEnvironmental protectionMedicinePathologyEcology

Abstract

fetched live from OpenAlex

In many countries around the world (including the United States, Canada, and Spain), research is being conducted into the impact of air pollution on the formation of various types of cancer. For a long time it was thought that the inhalation of pollutants could lead to lung diseases. Now the effects of air pollutants on tumors in the airways, kidneys, bladder, breast, and colon have been investigated and are better understood. It is now known that particulates in air pollution can cross the blood–brain barrier and also reach the placenta. The aim of this study was to find a possible relationship between the emission of pollutants into the atmosphere and the formation of specific types of tumors in the Polish population. Two databases available on the Internet were used in the analysis: the bank of measurement data on air quality in Poland (the repository of Environmental Protection Inspection) and cancer statistics. The pollution measurement data for the years 2000–2016 were taken from the Chief Inspectorate for Environmental Protection website, a database with results from 264 stations located in Poland for 13 types of gases and atmospheric pollutants. Statistical data on cancer C00–D09 (according to the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10)) in the Polish population in the years 1999–2015 were retrieved from onkologia.org.pl. A novel code was constructed, allowing the downloading of statistics from the databases, examination of their correlation, and selection of the best model of regression through machine learning. The results of the analyses indicate a high correlation of air pollution with the incidence of selected types of cancer. Particularly noteworthy is the observed effect of NOx on the incidence of small and large intestine cancers in the Masovia and West Pomerania provinces. The other gases and pollutants with the most significant impact on the incidence of gastrointestinal cancer have also been identified. Based on statistical analysis, we found a correlation between air pollution and tumor incidence in individual provinces, as well as an influence of the emission of nitrogen oxides on the cancer incidence rate.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.046
GPT teacher head0.306
Teacher spread0.259 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

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