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Record W2175504478 · doi:10.1177/0840470415607120

Si vous pensez que c’est juste un mal de jambe… détrompez-vous

2015· review· fr· W2175504478 on OpenAlexaffabout
Giuseppe Papia, Perry Mayer, D.F. Kelton, Douglas Queen, James A. Elliott, Janet L. Kuhnke

Bibliographic record

VenueHealthcare Management Forum · 2015
Typereview
Languagefr
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsSt. Lawrence CollegeLaurentian UniversityThe Mayer InstituteWilliam Osler Health SystemHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineHumanitiesArt

Abstract

fetched live from OpenAlex

Environ 800 000 Canadiens ont une maladie artérielle périphérique (MAP), une cause majeure d'amputation. Pourtant, le public et les cliniciens connaissent très peu cette maladie. Le présent article traite de la campagne de sensibilisation Si vous pensez que c'est juste un mal de jambe… détrompez-vous que l'Association canadienne du soin des plaies a lancée pour contrer cette tendance. Il porte également sur les facteurs de risque et le dépistage de la MAP, son lien avec le diabète, son traitement et ses soins, ses innovations en matière de soins de la MAP et la nécessité de faire preuve de leadership sur le plan des politiques.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.043
GPT teacher head0.340
Teacher spread0.298 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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