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Record W3118592936 · doi:10.1186/s12913-021-06065-4

Correction to: The patient advisor, an organizational resource as a lever for an enhanced oncology patient experience (PAROLEonco): a longitudinal multiple case study protocol

2021· article· en· W3118592936 on OpenAlexaff
Marie‐Pascale Pomey, Michèle de Guise, Mado Desforges, Karine Bouchard, Cécile Vialaron, Louise Normandin, Monica Iliescu‐Nelea, Isolda Fortin, Isabelle Ganache, Catherine Régis, Zeev Rosberger, Danielle Charpentier, Lynda Bélanger, Michel Dorval, Djahanchah Philip Ghadiri, Mélanie Lavoie‐Tremblay, Antoine Boivin, Jean‐François Pelletier, Nicolás Fernández, A. Danino

Bibliographic record

VenueBMC Health Services Research · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsInstitut Universitaire en Santé Mentale de QuébecHEC MontréalCentre Intégré de Santé et Services Sociaux de Chaudière-AppalacheJewish General HospitalCentre Hospitalier de l’Université de MontréalUniversité LavalUniversité de MontréalInstitut National d'Excellence en Santé et en Services SociauxCegep Edouard MontpetitCentre intégré de santé et de services sociaux de Chaudière-AppalachesMcGill University Health CentreMcGill UniversityHôpital Maisonneuve-RosemontCentre de réadaptation Lethbridge-Layton-Mackay
Fundersnot available
KeywordsHealth administrationHealth informaticsNursing researchMedicineProtocol (science)Surgical oncologyResource (disambiguation)Public healthLeverMedical educationNursingOncologyAlternative medicineComputer sciencePathologyEngineering

Abstract

fetched live from OpenAlex

An amendment to this paper has been published and can be accessed via the original article.

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)0.013
metaresearch head score (Gemma)0.210
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.210
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0050.003
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0070.014
Insufficient payload (model declined to judge)0.0550.021

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 head0.160
GPT teacher head0.555
Teacher spread0.395 · 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
GenreOther

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

Citations9
Published2021
Admission routes1
Has abstractyes

Explore more

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