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Record W1801919330 · doi:10.1002/pon.3618

2013 President's plenary international psycho‐oncology society: embracing the IPOS standards as a means of enhancing comprehensive cancer care

2014· article· en· W1801919330 on OpenAlexaff
Barry D. Bultz, Greta G. Cummings, Luigi Grassi, Luzia Travado, J. E. H. M. Hoekstra‐Weebers, Maggie Watson

Bibliographic record

VenuePsycho-Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsPlenary sessionPolitical scienceMedicineManagementOncologyInternal medicineLibrary scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: The second President's Plenary at the 2013 International Psycho-oncology Society's World Congress in Rotterdam, the Netherlands aimed to progress and, where needed, initiate changes to achieve comprehensive cancer care. Recent initiatives have been driven by the need to see psychosocial care as an integrated part of holistic multidisciplinary quality cancer care. The President's Plenary session covered the need for the following: An internationally agreed standard of quality cancer care, which includes psychosocial care for patients and their families and caregivers. An endorsement to assess distress as the 6th vital sign. Psycho-oncology professionals to integrate into a federation promoting better national and international outcomes. CONCLUSION: This overview highlights progress in terms of enhanced communication between and within different professionals groups supporting the implementation of a model of comprehensive patient care that is inclusive of psychosocial support and screening for distress. Tasks and challenges for the future are set out but the primary message is of the importance of collaboration in order to achieve recognition that psychosocial care is integrated into comprehensive cancer care; in this way, patient, family and carer needs can be more appropriately met.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.381
Teacher spread0.361 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations33
Published2014
Admission routes1
Has abstractyes

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