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Record W7099332047

Commentary

2006· article· en· W7099332047 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsnot available
Fundersnot available
KeywordsPertussis vaccineWhooping coughIncidence (geometry)PopulationBordetella pertussis
DOInot available

Abstract

fetched live from OpenAlex

type b conjugate vaccine (DTwP–IPV–Hib) to a combination vaccine containing acellular pertussis (DTaP–IPV–Hib). In this issue, Vickers and colleagues,1 using passive surveillance data from the Saskatoon Regional Health Authority in Saskatchewan for the period 1995–2005, report on their analy-sis of the effect of the change to the new vaccine on the inci-dence of pertussis among children less than 10 years of age. They found that, among infants (< 1 year old) and preschool children (aged 1–4 years), those who had received either the whole-cell pertussis vaccine or a combination of the whole-cell and acellular pertussis vaccines had a lower incidence of pertussis than those who had received only the acellular vac-cine; they found a reverse trend among children 5–9 years of age. Vickers and colleagues concluded that consideration be given to either modifying the current acellular pertussis vac-

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)0.004
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.870
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0040.002
Research integrity0.0270.013
Insufficient payload (model declined to judge)0.1300.047

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 head0.008
GPT teacher head0.222
Teacher spread0.214 · 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
Domainnot available
GenreCommentary

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
Published2006
Admission routes1
Has abstractyes

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