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Record W6950326901 · doi:10.5683/sp3/egfjpg

Knowledge, Perceptions, Awareness and Behaviours Relating to Immunization among First Nations and Inuit, 2011 [Canada]: First Nations File

2011· dataset· en· W6950326901 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2011
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPublic healthImmunizationDeveloping countryVaccine-preventable diseasesGlobal healthVaccinationHealth careDisease

Abstract

fetched live from OpenAlex

Health Canada's First Nations and Inuit Health Branch (FNIHB) is working with First Nations and Inuit communities to improve the health of First Nations people and Inuit living in Canada. As part of improving the health outcomes of First Nations people and Inuit, lowering the rates of vaccine preventable diseases is considered vital since vaccine preventable diseases such as pertussis, varicella and pneumococcal disease continue to be prevalent in First Nations and Inuit communities. The purpose of this survey is to provide Health Canada with research based information about the knowledge, perceptions, awareness and behaviours of First Nations people on-reserve and Inuit regarding immunization.

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.031
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.012
Science and technology studies0.0030.000
Scholarly communication0.0030.001
Open science0.0040.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0310.009

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 head0.019
GPT teacher head0.263
Teacher spread0.244 · 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 designObservational
Domainnot available
GenreDataset

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
Published2011
Admission routes1
Has abstractyes

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