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Record W4313453237 · doi:10.1136/thorax-2022-219539

Paediatric asthma hospitalisations continue to decrease in Finland and Sweden between 2015 and 2020

2023· article· en· W4313453237 on OpenAlexaff
Juho E. Kivistö, Jennifer L. P. Protudjer, Jussi Karjalainen, Anna Bergström, Heini Huhtala, Matti Korppi, Erik Melén

Bibliographic record

VenueThorax · 2023
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsGeorge & Fay Yee Centre for Healthcare InnovationUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
FundersVäinö ja Laina Kiven SäätiöTampereen TuberkuloosisäätiöFire Protection Research FoundationJalmari ja Rauha Ahokkaan Säätiö
KeywordsMedicineAsthmaIncidence (geometry)PediatricsDemographyInternal medicine

Abstract

fetched live from OpenAlex

We previously reported a decreasing incidence of paediatric asthma hospitalisations in Finland, but a rather stable trend in Sweden, between 2005 and 2014. We now aimed to investigate the incidence of paediatric asthma hospitalisations in these countries between 2015 and 2020, using Finland's National Hospital Discharge Register and Sweden's National Patient Register, which cover all hospitalisations in the respective countries. From 2015 to 2019, the incidence of paediatric asthma hospitalisations decreased by 36.7% in Finland and by 39.9% in Sweden and are increasingly approaching parity. In 2020, despite differences in COVID-19-related restrictions, asthma hospitalisations decreased by over 40%, thus warranting future research on the subject.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.308
Teacher spread0.291 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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