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Record W2903841734 · doi:10.14745/ccdr.v44i12a06

What is new in the Canadian Immunization Guide: November 2016 to November 2018

2018· article· en· W2903841734 on OpenAlexafffundvenueabout
Annie Fleurant, Matthew Tunis, Althea House

Bibliographic record

VenueCanada Communicable Disease Report · 2018
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsPublic Health Agency of Canada
FundersCanadian Armed ForcesHealth CanadaCenters for Disease Control and PreventionAssociation of Medical Microbiology and Infectious Disease CanadaPublic Health AgencyPublic Health Agency of Canada
KeywordsMedicineImmunizationMeaslesBreastfeedingFamily medicineHepatitis A vaccineAdvisory committeeHepatitis APublic healthVaccinationPediatricsImmunologyHepatitisNursingPolitical sciencePublic administration

Abstract

fetched live from OpenAlex

The Canadian Immunization Guide is an online resource that provides evidence-based recommendations on the use of vaccines and vaccine administration practices to health care providers and public health practitioners in Canada.Its contents are based on the most up-to-date recommendations of the National Advisory Committee on Immunization (NACI) and the Committee to Advise on Tropical Medicine and Travel (CATMAT).The Canadian Immunization Guide (CIG) is frequently updated online in response to new evidence and changing product indications.Between November 2016 and November 2018, new and updated recommendations were published for the chapters on Vaccine Administration Practices, Immunization of Immunocompromised Persons, and Immunization During Pregnancy and Breastfeeding and on seven active vaccines (for cholera and traveller's diarrhea, influenza, hepatitis A, hepatitis B, herpes zoster, human papillomavirus and pertussis), as well as a recent update on measles post-exposure prophylaxis.

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)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.074
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.010
Science and technology studies0.0040.002
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0740.033

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 head0.031
GPT teacher head0.326
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2018
Admission routes4
Has abstractyes

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