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Record W2145591421 · doi:10.3389/fonc.2014.00192

Collaborative Care in NSCLC; the Role of Early Palliative Care

2014· review· en· W2145591421 on OpenAlexaff
Marnie Howe, Ronald L. Burkes

Bibliographic record

VenueFrontiers in Oncology · 2014
Typereview
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineQuality of life (healthcare)Surgical oncologyMultidisciplinary approachPalliative careRadiation oncologyLung cancerPersonalized medicineSubtypingMultidisciplinary teamOncologyPrecision medicineDiseaseIntensive care medicineInternal medicineRadiation therapyMedical physicsPathologyNursingBioinformatics

Abstract

fetched live from OpenAlex

The management of non-small cell lung cancer (NSCLC) has evolved into a multidisciplinary team approach that traditionally has involved medical oncology, radiation oncology, and thoracic surgery. However, in the era of personalized medicine the importance of molecular diagnostics requires adequate tissue for histologic subtyping and molecular testing and thus requires the engagement of other subspecialties such as pathology, respirology, and interventional radiology. Unfortunately in 2014, the majority of patients presenting with NSCLC will succumb to their disease and the early integration of palliative care into the treatment strategy will improve the quality of life and end-of-life care of our patients and may in fact improve their overall survival.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.964
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.394
Teacher spread0.380 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2014
Admission routes1
Has abstractyes

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