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Record W4297464156 · doi:10.3390/curroncol29100555

Emerging Systemic Therapies in Advanced Unresectable Biliary Tract Cancer: Review and Canadian Perspective

2022· review· en· W4297464156 on OpenAlexafffundvenueabout
Vincent C. Tam, Ravi Ramjeesingh, Ronald L. Burkes, Eric M. Yoshida, Sarah Doucette, Howard J. Lim

Bibliographic record

VenueCurrent Oncology · 2022
Typereview
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsFluidigm (Canada)Vancouver General HospitalMount Sinai HospitalPrincess Margaret Cancer CentreDalhousie UniversityUniversity of Calgary
FundersAstraZeneca Canada
KeywordsMedicineGemcitabineBiliary tract cancerSystemic therapyOncologyCancerImmunotherapyIntensive care medicineTargeted therapyInternal medicineChemotherapyCisplatin

Abstract

fetched live from OpenAlex

Biliary tract cancer (BTC) is a group of rare and aggressive malignancies with a dismal prognosis. There is currently a significant lack in effective treatment options for BTC, with gemcitabine-cisplatin remaining the first-line standard of care treatment for over a decade. A wave of investigational therapies, including new chemotherapy combinations, immunotherapy, and biomarker-driven targeted therapy have demonstrated promising results in BTC, and there is hope for many of these therapies to be incorporated into the Canadian treatment landscape in the near future. This review discusses the emerging therapies under investigation for BTC and provides a perspective on how they may fit into Canadian practice, with a focus on the barriers to treatment access.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.961
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.135
GPT teacher head0.454
Teacher spread0.319 · 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
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

Citations13
Published2022
Admission routes4
Has abstractyes

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