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Record W2899369036 · doi:10.3747/co.25.3840

Current Landscape of Immunotherapy in the Treatment of Solid Tumours, with Future Opportunities and Challenges

2018· review· en· W2899369036 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCurrent Oncology · 2018
Typereview
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkLondon Health Sciences CentreHôpital Notre-Dame
Fundersnot available
KeywordsMedicineImmunotherapyClinical trialIntensive care medicineDiseaseBiomarkerStandard of careCancerInternal medicineBiology

Abstract

fetched live from OpenAlex

Immunotherapy has emerged as a new standard of care, showing survival benefit for solid tumours in multiple disease sites and indications. The survival improvements seen in diseases that were highly resistant to traditional therapies, with a poor prognosis, are unprecedented. Although the benefits observed in clinical trials are undeniable, not all patients derive those benefits, leading to emerging combination strategies and an ongoing quest for biomarker selection. Here, we summarize the current evidence for immunotherapy in the treatment of solid tumours, and we discuss emerging strategies at the forefront of research. We discuss future challenges that will be encountered as experience and knowledge continue to expand in this rapidly emerging field.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
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 head0.248
GPT teacher head0.435
Teacher spread0.187 · 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