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Record W2143225304 · doi:10.3201/eid1805.110235

Epidemic of Invasive Pneumococcal Disease, Western Canada, 2005–2009

2012· article· en· W2143225304 on OpenAlexafffundabout
Gregory J. Tyrrell, Marguerite Lovgren, Quazi Ibrahim, Sipi Garg, Linda Chui, Tyler J. Boone, Carol Mangan, David M. Patrick, Linda Hoang, Greg B. Horsman, Paul Van Caeseele, Thomas J. Marrie

Bibliographic record

VenueEmerging infectious diseases · 2012
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsUniversity of British ColumbiaBC Centre for Disease ControlSaskatchewan Disease Control LaboratoryUniversity of AlbertaDalhousie UniversityProvincial Laboratory of Public Health
FundersImperial College LondonUniversity of AlbertaWellcome Trust
KeywordsSerotypeMultilocus sequence typingOutbreakPneumococcal diseaseTypingPneumococcal infectionsDisease surveillanceMedicineVirologyDiseaseMolecular epidemiologyGenotypeBiologyStreptococcus pneumoniaeMicrobiologyInternal medicineGeneticsGene

Abstract

fetched live from OpenAlex

In Canada before 2005, large outbreaks of pneumococcal disease, including invasive pneumococcal disease caused by serotype 5, were rare. Since then, an epidemic of serotype 5 invasive pneumococcal disease was reported: 52 cases during 2005, 393 during 2006, 457 during 2007, 104 during 2008, and 42 during in 2009. Of these 1,048 cases, 1,043 (99.5%) occurred in the western provinces of Canada. Median patient age was 41 years, and most (659 [59.3%]) patients were male. Most frequently representing serotype 5 cases (compared with a subset of persons with non-serotype 5 cases) were persons who were of First Nations heritage or homeless. Restriction fragment-length polymorphism typing indicated that the epidemic was caused by a single clone, which multilocus sequence typing identified as sequence type 289. Large pneumococcal epidemics might go unrecognized without surveillance programs to document fluctuations in serotype prevalence.

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)0.001
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 score0.028
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.268
Teacher spread0.256 · 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

Citations30
Published2012
Admission routes3
Has abstractyes

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