MétaCan
Menu
← Back to cohort
Record W3095980742

ARTICLE HELENE HUDSON : Soutien apporté aux Autochtones, aux Inuits et aux Métis dans un service d’oncologie : mon expérience comme infirmière pivot attitrée

2020· article· fr· W3095980742 on OpenAlexaboutno aff
Carolyn Roberts, Gwen Barton, Allyson McDonald

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languagefr
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

J’ai passé ma jeunesse et une grande partie de ma carrière d’infirmière dans une région éloignée de la Basse-Côte-Nord du Québec. En tant qu’infirmière responsable d’une population d’environ 400 habitants, j’ai connu mon lot d’expériences risquées. Les dispensaires sont très différents des établissements de santé traditionnels. Il n’y a pas de laboratoire, pas de radiologie, pas d’ultrasons et parfois, pas de médecin. Le soutien vital de la communauté, ce sont les infirmières. Les urgences se produisent rarement au dispensaire, et transporter un patient à l’hôpital peut être extrêmement difficile. Cependant, une forte solidarité existe dans chaque village de la région. Les membres de la communauté peuvent être le plus grand atout dans le rétablissement des patients blessés ou malades. Ils sont votre bras droit, et parfois vos seuls bras en fait. J’ai transporté des patients en motoneige et en traîneau en hiver, sur une civière dans ma propre camionnette en été : mon style de soins infirmiers rime avec débrouillardise.

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)0.003
metaresearch head score (Gemma)0.011
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 score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.005
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0150.003

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 head0.573
GPT teacher head0.585
Teacher spread0.012 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)→Same topicGlobal Cancer Incidence and Screening→French-language works237,207→