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Record W4324143593 · doi:10.1016/j.esmoop.2023.101155

Anxiety and depression in adult cancer patients: ESMO Clinical Practice Guideline

2023· article· en· W4324143593 on OpenAlexaff
Luigi Grassi, Rosangela Caruso, Michelle B. Riba, Mari Lloyd‐Williams, David W. Kissane, Gary Rodin, Daniel C. McFarland, R. Campos-Ródenas, Robert Zachariae, Daniele Santini, Carla Ripamonti

Bibliographic record

VenueESMO Open · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsPrincess Margaret Cancer Centre
FundersEuropean Society for Medical Oncology
KeywordsAnxietyDepression (economics)MindfulnessGuidelineMedicineClinical psychologyCancerPsychiatryPopulationClinical PracticePsychologyInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

•Anxiety and depressive disorders are common in patients with cancer.•A higher prevalence seen in patients with cancer than the general population is often underrecognised.•Psychotherapy, cognitive behavioural therapy and mindfulness-based therapies are effective treatments.•Psychopharmacological treatments have been shown to be effective treatments of anxiety and depressive disorders.

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)0.006
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: Methods · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.005

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 head0.039
GPT teacher head0.424
Teacher spread0.385 · 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
GenreMethods

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

Citations259
Published2023
Admission routes1
Has abstractyes

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