MétaCan
Menu
Back to cohort
Record W2055979200 · doi:10.1593/tlo.11124

Moving Forward with Metronomic Chemotherapy: Meeting Report of the 2nd International Workshop on Metronomic and Anti-Angiogenic Chemotherapy in Paediatric Oncology

2011· article· en· W2055979200 on OpenAlexaff
Eddy Pasquier, Mark W. Kieran, Jaroslav Štěrba, Yuval Shaked, Sylvain Baruchel, Odile Oberlin, Maria Sanna Kivivuori, Andreas Peyrl, Mamouna Diawarra, Michela Casanova, Stergios Zacharoulis, Gilles Vassal, Franck Berthold, Arnauld Verschuur, Nicolás André

Bibliographic record

VenueTranslational Oncology · 2011
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineClinical trialClinical OncologyTerminologyOncologyChemotherapyCancerAlternative medicineInternal medicineIntensive care medicinePathology

Abstract

fetched live from OpenAlex

Metronomic chemotherapy, which is defined by the frequent, repetitive administration of chemotherapeutic drugs at relatively low doses, and without prolonged drug-free break, is an emerging strategy to fight cancer. Initially thought to act by targeting tumor angiogenesis, additional mechanisms have been recently unveiled, and metronomic chemotherapy is now considered to represent a form of multitargeted therapy. Despite representing a genuine alternative for advanced and/or high-risk cancer therapy, the development of metronomic approaches in pediatric oncology is still in the early stage. The few numbers of large-scale state-of-the-art clinical trials, issues regarding terminology and the limited understanding of the complex and intertwined mechanisms of action of metronomic treatments have limited progress in this important field of research. On March 18 and 19, 2010, the 2nd International Workshop on Metronomic and Anti-Angiogenic Chemotherapy in Paediatric Oncology was held in Marseille, France, and brought together clinicians, basic scientists, physician-scientists, trainees, and students from all around the world. The main aim of this international meeting was to provide a unique forum to 1) reflect on the major advances that have been made in this field of research since its creation, 2) communicate results from the most recent clinical trials and preclinical studies, 3) discuss the current and future challenges of the field, and 4) set forth a solid framework for future collaborative biologic and clinical studies. The present report documents the main preclinical and clinical data that were presented in the keynote and best abstract sessions and delivers the key messages from the meeting.

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)0.006
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0090.011
Insufficient payload (model declined to judge)0.0050.003

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 head0.028
GPT teacher head0.311
Teacher spread0.282 · 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

Citations38
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueTranslational OncologySame topicNeuroblastoma Research and TreatmentsFrench-language works237,207