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Record W2116425611 · doi:10.2217/ahe.11.52

European Society of Clinical Pharmacists International Workshop on Geriatrics

2011· article· en· W2116425611 on OpenAlexaffabout
Louise Mallet, Annemie Somers

Bibliographic record

VenueAging Health · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsGeriatricsAttendanceMedicineFamily medicineCare of the elderlyPharmacistDementiaGeriatric careGerontologyMedical educationPharmacyNursingPsychiatryPolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

The European Society of Clinical Pharmacists (ESCP)held its third annual international meeting on May 5 and 6 in Utrecht in The Netherlands. This year the focus was on geriatrics. It was chaired by Louise Mallet (Montreal, Canada) who coordinated the scientific committee, which included Annemie Somers (Belgium), Ulrika Gillese (Sweden), Marcel Bouvy (The Netherlands), Hannelore Kreckel (Germany), Erik Gerbrands (The Netherlands) and Piera Polidori (Italy). The attendance was mainly composed of clinical pharmacists who have an interest in geriatrics. A number of the 110 participants were present at this workshop from different countries around the world. The 2-day meeting was organized around plenary sessions, interactive workshop sessions, oral communications and poster presentations. The plenary sessions explored four topics, namely the appropriateness of prescribing in older patients, the specific needs for research in geriatrics, frailty in the elderly and an update on dementia in the elderly. Cecilia Bernsten, president of ESCP, welcomed the participants on May 5 by emphasizing the growing role of pharmacists in taking care of older patients.

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)0.009
metaresearch head score (Gemma)0.008
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0330.011

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 head0.741
GPT teacher head0.543
Teacher spread0.197 · 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
GenreOther

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
Published2011
Admission routes2
Has abstractyes

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