MétaCan
Menu
Back to cohort
Record W2744268113 · doi:10.5737/23688076273243250

Peur de la recidive : Etude de l’experience vecue par les survivantes du cancer des ovaires

2017· article· fr· W2744268113 on OpenAlexaffvenue
Jamie Kyriacou, Alex Black, Nancy Drummond, Joanne Power, Christine Maheu

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2017
Typearticle
Languagefr
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsMcGill University Health CentreJewish General HospitalMontreal General HospitalMcGill University
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Objectif : L’objectif de la présente étude est de mieux comprendre la peur de la récidive à la lumière de l’expérience vécue par des survivantes du cancer des ovaires et des trompes de Fallope. Méthodologie : L’étude fait appel à un devis descriptif qualitatif. Douze participantes en rémission d’un cancer des ovaires ou des trompes de Fallope ont été recrutées. Les chercheuses ont d’abord procédé à des entrevues semi-structurées en personne puis analysé le contenu et les retranscriptions textuelles des entretiens. Résultats : La peur de la récidive est une préoccupation non négli- geable chez les femmes en rémission d’un cancer des ovaires. Quatre thèmes ressortent de l’expérience vécue par les participantes à cet égard : a) incertitude entourant la récidive; b) croyances et sources d’inquiétude variées; c) risque de récidive perçu; d) gestion de la peur de la récidive. Implications : Les in rmières peuvent optimiser le soutien apporté aux survivantes en restant à l’a ût de cette peur de la récidive, en o rant de l’aide psychosociale aux femmes risquant de vivre cette peur, ainsi qu’en enseignant et en renforçant les stratégies d’adaptation.

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)0.017
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.035
GPT teacher head0.374
Teacher spread0.339 · 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
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Oncology Nursing JournalSame topicCancer survivorship and careFrench-language works237,207