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Record W14744661 · doi:10.1080/08958370490258129

Influencia de distintos factores ambientales sobre la producción de leche de la cabra criolla serrana argentina

2002· article· en· W14744661 on OpenAlexaboutno aff
José Luís Fernández, A.E. Rabasa, Daniel Hernández, Silvina A. Saldaño, F. D. Holgado, Poli

Bibliographic record

VenueInhalation Toxicology · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLivestock Farming and Management
Canadian institutionsnot available
Fundersnot available
KeywordsBiology

Abstract

fetched live from OpenAlex

To assess the association between relatively low levels of size-fractioned particulate matter (PM) and hospitalization for chronic obstructive pulmonary disease (COPD), we conducted a time-series analysis among elderly people 65 yr of age or more living in Vancouver between June 1995 and March 1999. Measures of thoracic PM (PM(10)), fine PM (PM(2.5)), coarse PM (PM(10-2.5)), and coefficient of haze (COH) were examined over periods varying from 1 to 7 days prior to hospital admissions. Generalized additive models (GAMs; general linear models, GLMs) were used, and temporal trends and seasonal and subseasonal cycles in COPD hospitalizations were removed by using GLM with parametric natural cubic splines. The relative risks were calculated based on an incremental exposure corresponding to the interquartile range of these measures, and were adjusted for daily weather conditions and gaseous pollutants. PM measures had a positive effect on COPD hospitalization, especially 0 to 2 days prior to the admissions, before copollutants were accounted for. For 3-day average levels of exposure the relative risk estimates were 1.13 (95% confidence interval: 1.05-1.21) for PM(10), 1.08 (1.02-1.15) for PM(2.5), 1.09 (1.03-1.16) for PM(10-2.5), and 1.05 (1.01-1.09) for COH. The associations were no longer significant when NO(2) was included in the models. We concluded that the particle-related measures were significantly associated with COPD hospitalization in the Vancouver area, where the level of air pollution is relatively low, but the effects were not independent of other air pollutants.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.241
Teacher spread0.223 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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