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Record W4249394145 · doi:10.1097/cco.0000000000000586

Editorial introductions

2019· article· en· W4249394145 on OpenAlexaboutno aff

Bibliographic record

VenueCurrent Opinion in Oncology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerOncologyClinical OncologyAssociate editorLibrary scienceInternal medicineFamily medicineMedical educationCancer

Abstract

fetched live from OpenAlex

Current Opinion in Oncology was launched in 1989. It is one of a successful series of review journals whose unique format is designed to provide a systematic and critical assessment of the literature as presented in the many primary journals. The field of psychiatry is divided into 15 sections that are reviewed once a year. Each section is assigned a Section Editor, a leading authority in the area, who identifies the most important topics at that time. Here we are pleased to introduce the Journal's Section Editors for this issue. SECTION EDITORS Giuseppe CuriglianoGiuseppe CuriglianoGiuseppe Curigliano, MD PhD, is Associate Professor of Medical Oncology at University of Milan, Italy, and the Head of the Division of Early Drug Development at European Institute of Oncology, Italy. He is a clinician and researcher specializing in early drug development for patients with solid tumors with a special commitment to breast cancer. He has been an ESMO Breast Faculty Member since 2001 and served on the Program Scientific Committee of the St Gallen Conference since 2011, and as Scientific Chair in St Gallen in 2017 and 2019. He has been appointed as Editor of Annals of Oncology for the period 2014–2018 and 2018–2020, and serves as co-Editor-in-Chief of The Breast, co-Editor-in-Chief of Cancer Treatment Reviews, Associate Editor of the European Journal of Cancer, as well as Editor of the Journal of Clinical Oncology and Current Opinion in Oncology. He also serves on the European School of Oncology (ESO) faculty committee. Dr Curigliano serves ESMO as a member of the ESMO Press & Media Affairs Committee, and has been in the ESMO Women for Oncology Committee, the ESMO Membership and ESMO Global Policy Committees since 2016. He was elected as member of the ESMO Nominating Committee in 2017. He served as the scientific chair of the IMPAKT meeting that was held in Brussels in 2014 and as the Breast Cancer (metastatic) Track Chair of the ESMO 2014 meeting in Madrid. He acted as co-chair for the first ESMO Breast Cancer Congress in 2019. Dr Curigliano was awarded with the first ESO Umberto Veronesi Award in Vienna in 2017 and with the Fellowship of the European Academy of Cancer Sciences in Paris in 2017. He has contributed to over 300 peer-reviewed publications. Marc SansonMarc SansonDr Marc Sanson, MD, PhD is Professor at Sorbonne Université, Paris, France. He is active in clinical neuro-oncology at the Department of Neurology 2, Pitié-Salpêtrière Hospital in France. He is also head of the research team ‘experimental neuro-oncology’ at the Institut du Cerveau et de la Moelle (ICM), France. Dr Sanson is the Director of the recently created “CURAMUS” site of Sorbonne-Université, which is one of the eight French Sites for Integrated Research on Cancer (SiRIC). Dr Sanson has published many research articles on neuro-oncology, including more than 200 dedicated to gliomas, as well as book chapters, and is a frequently requested lecturer on this topic. His main interest is focused on clinical and translational research on gliomas, including novel targeted therapies, germline and somatic genetic characterisation and development of new biomarkers. He is a reviewer on a number of journals, including the Journal of Clinical Oncology, Lancet, Lancet Oncology, Annals of Oncology, Annals of Neurology, Neurology, Cancer, Clinical Cancer Research, Cancer Research and Acta Neuropathologica. Dr Sanson earned his MD at University R Descartes and his PhD at University D Diderot, both in Paris, France. He completed a residency in Neurology in Paris, and a post-doctoral stage at McGill University, Canada. Miguel A. SanzMiguel A. SanzDr Miguel A. Sanz is Researcher Emeritus of the Instituto de Investigación Sanitaria La Fe, Spain, and Honorary Professor of the Department of Medicine at the University of Valencia, Spain. After earning his medical degree at the University of Salamanca, Spain, he was intern, resident and subsequently completed a fellowship in Hematology at the University Hospital La Fe. He was appointed as Head of the Clinical Hematology Section to the University Hospital La Fe in 1977 and then later promoted to Head of the Hematology Department in 2007 as well as Full Professor of Medicine at the University of Valencia. Professor Sanz is Chairman of the Spanish PETHEMA Group and leads the Working Parties of acute promyelocytic leukemia and infections in neutropenic patients. He is currently a reviewer for numerous high-profile medical journals, including all top hematology journals, and has authored more than 550 peer-reviewed papers, numerous book chapters, and in excess of 1100 abstracts at national and international meetings. Prof. Sanz has also lectured widely in Europe, North, central and South America, as well as in the Middle East and Asia, serving as lecturer at the American Society of Hematology and European Hematology Association meetings in several occasions.

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)0.008
metaresearch head score (Gemma)0.076
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.191
Threshold uncertainty score0.638

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.076
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.002
Science and technology studies0.0030.002
Scholarly communication0.0090.005
Open science0.0030.003
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.1910.127

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 head0.054
GPT teacher head0.414
Teacher spread0.360 · 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
GenreEditorial

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

Citations0
Published2019
Admission routes1
Has abstractyes

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