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Record W2802554856 · doi:10.1136/oemed-2017-104955

Greater coordination and harmonisation of European occupational cohorts is needed

2018· editorial· en· W2802554856 on OpenAlexaff
Michelle C. Turner, Ingrid Sivesind Mehlum

Bibliographic record

VenueOccupational and Environmental Medicine · 2018
Typeeditorial
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsUniversity of Ottawa
FundersGeneralitat de CatalunyaEuropean Cooperation in Science and TechnologyDepartament de Salut, Generalitat de CatalunyaCentres de Recerca de Catalunya
KeywordsUnderemploymentWorkforceEnvironmental healthPopulationMedicineUnemploymentPsychological interventionBusinessDemographic economicsGerontologyEconomic growthEconomics

Abstract

fetched live from OpenAlex

Paid employment is an essential component of adult life and a major determinant of health. However, underemployment, long-term unemployment, poor working conditions and a lack of job security all negatively affect health, may hinder economic growth and further increase inequalities in the population. Occupational exposures are related to a significant proportion of diseases including cancer, cardiorespiratory diseases and musculoskeletal and mental disorders, among others.1 The demographic shift, with an ageing and increasingly diverse workforce, makes the impact of work on healthy ageing and disease prognosis a key issue. Rapid changes in employment patterns and exposures along with occupational restructuring and the increasing use of new technologies further increase the importance of research in occupational health.

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)0.048
metaresearch head score (Gemma)0.088
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.952
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.088
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0040.002
Science and technology studies0.0010.002
Scholarly communication0.0060.009
Open science0.0050.005
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.0230.010

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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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.

Study designNot applicable
DomainMethods
GenreEditorial

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

Citations27
Published2018
Admission routes1
Has abstractyes

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