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Record W2478057664 · doi:10.4324/9780429271038-6

Caffeine and arousal: a biobehavioral theory of physiological, behavioral, and emotional effects

2020· article· en· W2478057664 on OpenAlexaboutno aff
Barry D. Smith, Kenneth Tola, Mark Mann

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsnot available
Fundersnot available
KeywordsCaffeineArousalPsychologyPsychoactive substanceMedicinePsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Over 50% of both high school and college students report experience with illicit drugs, and 27% of all Americans abuse drugs at some time in their lives. 1 In fact, 20 million people in the United States reported heavily using and abusing drugs in 1994. 2 Some of these drugs, including cocaine and the amphetamines, are stimulants that increase arousal and provide the user with a psychological “high.” But cocaine, for example, was used by only 3.6% of the U.S. populace in 1994, 3 as compared with the 80% of U.S. adults who drink coffee or tea daily. The average adult in the U.S. and Canada consumes 4 mg/kg/day, 4 and many exceed 15 mg/kg. 5,6 Similarly, Asians and some Europeans consume large amounts of caffeine in tea. Coffee contains a larger amount of caffeine, averaging 85 mg for ground roasted and 60 mg for instant in 5 oz, while leaf tea (5 oz) averages 30 mg and instant tea averages 20. 7

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.925
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

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

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 head0.091
GPT teacher head0.360
Teacher spread0.268 · 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.

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

Citations7
Published2020
Admission routes1
Has abstractyes

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