MétaCan
Menu
Back to cohort
Record W3024575601

[Delegation of medico-administrative tasks : what do medical interns and secretaries think?]

2017· article· en· W3024575601 on OpenAlexaff
Julien Castioni, Angélique Hagenbuch, Johann Tâche, Milva Cappai, Milica Jovanović, Cláudio Sartori

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsEmployment and Social Development Canada
Fundersnot available
KeywordsContext (archaeology)DelegationPolitical scienceHumanitiesLibrary scienceBusinessNursingMedicineHistoryArtComputer scienceLawArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The hospital activity of physicians in training mainly consists in direct contacts with patients, tasks indirectly linked to patients such as administration, as well as clinical and theoretical training. In our era of digitalization, an important administrative work load without any added medical value fills their daily chores. In parallel activities of medical secretaries are getting more partitioned, with their desks situated far from physicians' and tasks often limited to finalizing discharge letters. Added to multiple overtime, this reduces physicians' and secretaries' work satisfaction. This article describes the context and development of delegating medico-administrative tasks to secretaries in our department of internal medicine.

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)0.005
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.114
GPT teacher head0.432
Teacher spread0.318 · 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 designQualitative
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

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicHealth, Medicine and SocietyFrench-language works237,207