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Record W2055638886 · doi:10.1080/07448481.2012.700973

2009–2010 Seasonal Influenza Vaccination Coverage Among College Students From 8 Universities in North Carolina

2012· article· en· W2055638886 on OpenAlexaboutno aff
Katherine A. Poehling, Jill N. Blocker, Edward H. Ip, Timothy R. Peters, Mark Wolfson

Bibliographic record

VenueJournal of American College Health · 2012
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institute on Alcohol Abuse and Alcoholism
KeywordsSeasonal influenzaInfluenza vaccineVaccinationMedicineQuarter (Canadian coin)Family medicineDemographyReceiptEnvironmental healthGerontologyCoronavirus disease 2019 (COVID-19)ImmunologyGeographyDiseaseInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The authors sought to describe the 2009-2010 seasonal influenza vaccine coverage of college students. PARTICIPANTS: A total of 4,090 college students from 8 North Carolina universities participated in a confidential, Web-based survey in October-November 2009. METHODS: Associations between self-reported 2009-2010 seasonal influenza vaccination and demographic characteristics, campus activities, parental education, and e-mail usage were assessed by bivariate analyses and by a mixed-effects model adjusting for clustering by university. RESULTS: Overall, 20% of students (range 14%-30% by university) reported receiving 2009-2010 seasonal influenza vaccine. Being a freshman, attending a private university, having a college-educated parent, and participating in academic clubs/honor societies predicted receipt of influenza vaccine in the mixed-effects model. CONCLUSIONS: The self-reported 2009-2010 influenza vaccine coverage was one-quarter of the 2020 Healthy People goal (80%) for healthy persons 18 to 64 years of age. College campuses have the opportunity to enhance influenza vaccine coverage among its diverse student populations.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.375
Teacher spread0.338 · 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

Citations37
Published2012
Admission routes1
Has abstractyes

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