MétaCan
Menu
Back to cohort
Record W2736952847 · doi:10.4251/wjgo.v9.i7.281

Evolving treatment landscape for early and advanced pancreatic cancer

2017· review· en· W2736952847 on OpenAlex
Sally C. M. Lau, Winson Y. Cheung

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWorld Journal of Gastrointestinal Oncology · 2017
Typereview
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsFOLFIRINOXMedicineGemcitabinePancreatic cancerContext (archaeology)OncologyInternal medicineStage (stratigraphy)CancerPaclitaxelAdenocarcinomaIrinotecanColorectal cancer

Abstract

fetched live from OpenAlex

Pancreatic ductal adenocarcinoma is an infrequent cancer with a high disease related mortality rate, even in the context of early stage disease. Until recently, the rate of death from pancreatic cancer has remained largely similar whereby gemcitabine monotherapy was the mainstay of systemic treatment for most stages of disease. With the discovery of active multi-agent chemotherapy regimens, namely FOLFIRINOX and gemcitabine plus nab-paclitaxel, the treatment landscape of pancreatic cancer is slowly evolving. FOLFIRINOX and gemcitabine plus nab-paclitaxel are now considered standard first line treatment options in metastatic pancreatic cancer. Studies are ongoing to investigate the utility of these same regimens in the adjuvant setting. The potential of these treatments to downstage disease is also being actively examined in the locally advanced context since neoadjuvant approaches may improve resection rates and surgical outcomes. As more emerging data become available, the management of pancreatic cancer is anticipated to change significantly in the coming years.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.000
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 head0.136
GPT teacher head0.468
Teacher spread0.332 · 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