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Record W7135739433

The impact of advertisement and promotion of alternative tobacco and nicotine products on tobacco users: online survey

2023· dissertation· cs· W7135739433 on OpenAlexaboutno aff
Alžběta Jirásková

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2023
Typedissertation
Languagecs
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
Fundersnot available
KeywordsCzechNicotinePoint of saleQuarter (Canadian coin)PopulationPromotion (chess)LegislationSnus
DOInot available

Abstract

fetched live from OpenAlex

Background: In the last few years, a large number of nicotine products have appeared on the Czech market, which are intended, among other things, to serve as alternatives to conventional cigarettes. These alternatives are often visually very distinctive and attractive. They are often perceived by users as less harmful and suitable for substitution for conventional cigarettes. At the same time, these products are not subject to legislation as strict as conventional cigarettes or packaged tobacco. Currently, approximately one quarter of the Czech population are at least occasional smokers, and a significant proportion are either currently using alternative nicotine products or are considering changing their use. Aims: The main objective of this work was to determine how active tobacco users perceive new alternatives on the market, specifically in terms of health harms, marketing presentation and appearance. In particular, another objective is to map preferences in the choice of use form and to compare the above mentioned alternatives with conventional cigarettes. Methods: The data was obtained through quantitative research. It was carried out using an online questionnaire survey in the Survio platform interface and distributed in the social networking environment. Respondents were collected through...

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)0.002
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.325
Teacher spread0.294 · 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
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

Citations0
Published2023
Admission routes1
Has abstractyes

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