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Record W3135342425 · doi:10.46290/cjok000012

Non-Pharmaceutical Interventions

2021· article· en· W3135342425 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCascade Journal of Knowledge · 2021
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsPsychological interventionPresentation (obstetrics)Social distancePandemicCoronavirus disease 2019 (COVID-19)PsychologyMedicineDiseaseInfectious disease (medical specialty)Nursing

Abstract

fetched live from OpenAlex

The purpose of the presentation is to briefly describe what non-pharmaceutical interventions are and how the NPIs are particularly critical in the early stages of the spreading of conventional and especially pandemic influenzas flus. The presentation indicate that non-pharmaceutical interventions (NPIs) consist of Personal protective measures for everyday use, personal protective measures reserved for influenza pandemics, environmental measures and community measures aimed at increasing social distancing. Furthermore, the presentation discusses the spreading of the viruses and how the NPIs can alleviate the negative impacts of the virus before effective vaccinations become available. Some practical examples about the use of NPIs are demonstrated.

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.

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)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.422
GPT teacher head0.529
Teacher spread0.107 · 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