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Record W2078570464 · doi:10.1177/0091270010393344

A Review of Psychophysiological Stressors on Pharmacokinetics

2011· review· en· W2078570464 on OpenAlexaffabout
Henry T. Peng, Bob Cheung

Bibliographic record

VenueThe Journal of Clinical Pharmacology · 2011
Typereview
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsPharmacokineticsStressorDrugMedicinePharmacologyClinical psychology

Abstract

fetched live from OpenAlex

We conducted a comprehensive literature review on the effects of psychophysiological stressors on the pharmacokinetics of drugs commonly used by the Canadian Forces. These stressors may change the physiological status of an individual and subsequently may alter the drug's pharmacokinetics. The effects of isolated physical activities on pharmacokinetics have been well documented. However, the findings are inconsistent due to variations in the intensity and duration of the activity, and the routes and timing of drug administration. The effects of other environmental stressors, such as temperature extremes, hypobaric, hyperbaric, hyperoxic conditions, and the effects of multiple stressors are less well known. There are limited studies describing the effects of psychological stressors on drug pharmacokinetics. Further studies are necessary to understand the clinical implications of pharmacokinetic changes. We also discussed the advantage of using a physiologically based pharmacokinetic model to predict the effects of a single or multiple stressors.

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)0.004
metaresearch head score (Gemma)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.869
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.348
GPT teacher head0.580
Teacher spread0.233 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2011
Admission routes2
Has abstractyes

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