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Record W2046257359 · doi:10.1177/0091270005280297

Aging and Clinical Pharmacology: Implications for Antidepressants

2005· review· en· W2046257359 on OpenAlexaff
Francis E. Lotrich, Bruce G. Pollock

Bibliographic record

VenueThe Journal of Clinical Pharmacology · 2005
Typereview
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsBaycrest Hospital
FundersNational Institute of Mental Health
KeywordsAntidepressantMedicineClinical trialDepression (economics)PolypharmacyAdverse effectClinical pharmacologyPharmacokineticsIntensive care medicinePsychiatryPharmacologyInternal medicineAnxiety

Abstract

fetched live from OpenAlex

The elderly frequently have changes in pharmacokinetics, sensitivity to medications, homeostatic reserve (ability to tolerate physiological challenges), exposure to multiple medications, and adherence. All of these age-associated factors can potentially influence total exposure to medication, adverse effects, and subsequent treatment outcome. Most clinical trials are performed with healthy, younger adults. Extrapolating the results of these trials to the elderly may be inappropriate, particularly for the antidepressant treatment of depression. The authors review these age-associated differences and discuss their implications for antidepressant use in older adults.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.323
GPT teacher head0.623
Teacher spread0.300 · 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 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

Citations108
Published2005
Admission routes1
Has abstractyes

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