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Record W4390694489 · doi:10.1016/j.ijrobp.2024.01.010

Combinatorial Approaches for Chemotherapies and Targeted Therapies With Radiation: United Efforts to Innovate in Patient Care

2024· article· en· W4390694489 on OpenAlexaff
Salma K. Jabbour, Ritesh Kumar, Bethany Anderson, Junzo Chino, Krishan R. Jethwa, Lachlan McDowell, Andrea Lo, Dawn Owen, Erqi L. Pollom, Alison Tree, Derek S. Tsang, Sue S. Yom

Bibliographic record

VenueInternational Journal of Radiation Oncology*Biology*Physics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkBC Cancer Agency
FundersNational Cancer InstituteBeiGeneStrykerAstraZeneca
KeywordsMedicineDiseaseRadiation therapyDisease controlIntensive care medicineSystemic therapyInternal medicineCancerEnvironmental health

Abstract

fetched live from OpenAlex

Combinatorial therapies consisting of radiation therapy (RT) with systemic therapies, particularly chemotherapy and targeted therapies, have moved the needle to augment disease control across nearly all disease sites for locally advanced disease. Evaluating these important combinations to incorporate more potent therapies with RT will aid our understanding of toxicity and efficacy for patients. This article discusses multiple disease sites and includes a compilation of contributions from expert Red Journal editors from each disease site. Leveraging improved systemic control with novel agents, we must continue efforts to study novel treatment combinations with RT.

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)0.010
metaresearch head score (Gemma)0.007
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: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0080.002

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 head0.014
GPT teacher head0.299
Teacher spread0.285 · 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
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

Citations8
Published2024
Admission routes1
Has abstractyes

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