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Record W4255668954 · doi:10.1037//0021-843x.110.1.59

Is smoking automatic? Demands of smoking behavior on attentional resources.

2001· article· en· W4255668954 on OpenAlexaff
Bruce W. Baxter, Riley E. Hinson

Bibliographic record

VenueJournal of Abnormal Psychology · 2001
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyBaseline (sea)SmokeTask (project management)Cigarette smokingClinical psychologyAudiologyDevelopmental psychologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

The role of attention in the production of smoking behavior was investigated. Experienced and novice smokers were asked to perform a reaction time (RT) task under 4 conditions: while smoking (smoking), while mimicking all aspects of smoking except inhaling (pseudosmoking), while simply holding a cigarette (holding), and while not smoking (baseline). Experienced smokers' RTs increased during the pseudosmoking and holding conditions compared with baseline but did not differ between the smoking and baseline conditions, suggesting that attentional resources were not required for typical smoking behavior but were required to alter or inhibit smoking behavior. Novice smokers' RTs were slower during both the smoking and pseudosmoking conditions but not the holding condition, suggesting that novice smokers require the use of resources to smoke. Experiment 2 demonstrated that the differences in RT across conditions could not be explained by differences in urges.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.089
GPT teacher head0.432
Teacher spread0.344 · 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

Citations10
Published2001
Admission routes1
Has abstractyes

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