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Record W2118170536

L’automatisation en l’an 2000

2000· article· fr· W2118170536 on OpenAlexaffabout
Eva Cohen, Sandra Serour, Michael Zelovics

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsHumanitiesArtPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Resume Le departement de pharmacie de l’Hopital general juif — Sir Mortimer B. Davis, de Montreal, a modifie sa distribution manuelle des medicaments pour un systeme automatise. Cette nouvelle technologie semble soulager les pharmaciens de leurs tâches techniques pour accroitre la qualite des soins pharmaceutiques offerts aux patients. Le manque de personnel dans notre departement a ete prouve et nous a encourage a faire une demande ecrite aupres de l’hopital afin de permettre l’acquisition d’un systeme automatise. Apres acceptation de notre demande, nous avons choisi le systeme FDS-330 d’AutoMed™. Dans notre departement, l’automatisation a permis : • aux pharmaciens de sauver 9,5 heures de leur temps quotidien et de maximiser les taches journalieres des assistants-techniques • de centraliser les stocks, donc de reduire l’inventaire physique. • d’assurer une distribution fiable des medicaments avec un taux d’erreur inferieur a 0,1 %. L’automatisation a eu un impact positif sur notre departement tant sur le plan technique que professionnel. Abstract The pharmacy department of Sir Mortimer B. Davis-Jewish General Hospital, in Montreal, has modified its manual distribution of drugs for an automated system. This new technology seems to relieve pharmacists of their technical tasks to increase the quality of pharmaceutical care offered to patients. Understaffing in our department has been demonstrated and proven and has encouraged us to make a request in writing towards the hospital for the acquisition of an automated dispensing system. After approval of our request, we have selected the AutoMed™ FDS-330 system. In our department, automation has allowed: • Pharmacists to save 9.5 hours of their daily time while maximizing the daily tasks of the technician. • To centralize inventory, therefore reduce the physical inventory. • To maintain a reliable distribution of drugs with an error ratio lower than 0.1%. The automation has shown a positive impact on our department technically and professionally.

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)0.006
metaresearch head score (Gemma)0.014
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: Commentary · Consensus signal: none
Teacher disagreement score0.132
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0470.022

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 head0.108
GPT teacher head0.420
Teacher spread0.312 · 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
GenreCommentary

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

Citations2
Published2000
Admission routes2
Has abstractyes

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