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Record W4390577242 · doi:10.1055/s-0043-1777703

Palliative Care in Neuro-oncology

2024· article· en· W4390577242 on OpenAlexaboutno aff
Jessica Besbris, Lynne P. Taylor

Bibliographic record

VenueSeminars in Neurology · 2024
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePalliative careIntensive care medicineOncologyNursing

Abstract

fetched live from OpenAlex

Historically, the practice of neurology as an independent subspecialty from internal medicine began in Europe and the United States in the 1930s. The American Academy of Neurology (AAN) was founded 75 years ago in 1948, solidifying its emergence as a stand-alone discipline of medicine. In 1967, St. Christopher's Hospice, the first free standing hospice home, was opened in London by Dame Cicely Saunders. Dame Saunders is considered a pioneer in the development of the hospice movement, and she embodies the importance of the multi-disciplinary team in the care of the patient, as she began her career as a nurse, then became a social worker and, finally, a physician. A decade later, in 1978, Dr. Balfour Mount, a Canadian urologic cancer surgeon, coined the term "palliative care" ("to improve the quality of life") after having spent time with Dr. Saunders at St. Christopher's some years earlier. The field of palliative care continued to develop as a distinct subspecialty focused on improving quality of life for patients at any age and in any stage of serious illness. In a 1996 position statement, the AAN made clear that the practice of primary palliative care is the responsibility of all neurologists to their patients. Finally, coming full circle, the specialty of neuro-palliative care, a subspecialty not just of neurology but of palliative medicine, became established around 2018. Neuro-palliative care can be seen as a specialty focusing on the holistic approach to symptom management in patients suffering from neurologic disease with the aim of improved symptom control and attention to the psychologic and spiritual aspects of illness.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.842
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.066
GPT teacher head0.421
Teacher spread0.356 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2024
Admission routes1
Has abstractyes

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