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Record W3180347278 · doi:10.7731/kifse.43e071b7

Study on Thermal Accumulation Risk of e-Cigarettes According to Heating Coil Shape

2021· article· en· W3180347278 on OpenAlexaff
Jin‐Sun Kim, Sung Woo Kim, Seong-Pil Kwon

Bibliographic record

VenueFire Science and Engineering · 2021
Typearticle
Languageen
FieldNursing
TopicNutrition, Health and Food Behavior
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsElectromagnetic coilDegree (music)ThermalMaterials scienceChemistryAnalytical Chemistry (journal)ThermodynamicsElectrical engineeringChromatographyAcousticsPhysics

Abstract

fetched live from OpenAlex

In this study, factors affecting the degree of heat accumulation and amount of carbonyl compound production of e-cigarettes were studied. Structurally, e-cigarettes consist of an electronic circuit device and a cartomizer. The liquid solution of the e-cigarette is vaporized by a coil in the cartomizer, where heat accumulation and carbonyl compound production occur. The relationship between the two were analyzed according to the shape of the coil. X-ray images of the coil shapes within the cartomizer were obtained and classified according to the relative widths of the coils. The degree of heat accumulation and amount of carbonyl compound generation were examined via inhale and exhale tests. The relationships among the relative width of the coil, degree of heat accumulation, and amount of carbonyl compound generation were derived. For optimal design of the cartomizer, it is suggested that the relative width of the coil be set to to 5 or more.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
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 head0.041
GPT teacher head0.322
Teacher spread0.281 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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