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Record W2931365394 · doi:10.18332/tpc/105272

Error Correction Model Analysis of Tobacco Consumption in Kosovo

2019· article· en· W2931365394 on OpenAlexfundno aff
Jeta Statovci

Bibliographic record

VenueTobacco Prevention & Cessation · 2019
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
FundersThird Health ProgrammeUniversity of WaterlooCanadian Institutes of Health ResearchEuropean Commission
KeywordsConsumption (sociology)Error correction modelTobacco useStatisticsEnvironmental healthEconometricsMedicineEconomicsMathematicsSociologyCointegration

Abstract

fetched live from OpenAlex

Information for cigarette consumption during the time period 2005-2017, was utilized to assess the price and income elasticity effects on smoking intensity in Kosovo. The analysis was conducted by applying the error-correction model to estimate both the long-term and short-term smokers’ sensitivity to changes in price and income. The study revealed that the short run price elasticity is -0.33, and -0.68 in the long run. Contrary to the price effect, income showed positive correlation to cigarette consumption in Kosovo. Based in the information revealed, it can be concluded that increasing taxes on cigarette results in lower consumption at the macro level.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.322
Teacher spread0.286 · 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.

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
Published2019
Admission routes1
Has abstractyes

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