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Record W2576787462 · doi:10.1016/j.breast.2017.01.001

Corrigendum to “3rd ESO-ESMO international consensus guidelines for advanced breast cancer (ABC 3)” [Breast 31 (February 2017) 244–259]

2017· erratum· en· W2576787462 on OpenAlexaff
Fátima Cardoso, A. Costa, Elżbieta Senkus, Matti Aapro, Fabrice André, Carlos H. Barrios, Jonas Bergh, G.S. Bhattacharyya, Laura Biganzoli, M. Jorge Cardoso, L. Carey, D. Corneliussen-James, Giuseppe Curigliano, Véronique Dièras, N. El Saghir, A. Eniu, Lesley Fallowfield, D. Fenech, Prudence A. Francis, K. Gelmon, Alessandra Gennari, N. Harbeck, Clifford A. Hudis, B. Kaufman, IE Krop, Musa Mayer, Hanneke Meijer, Shirley Mertz, Shinji Ohno, O. Pagani, Efthymios Papadopoulos, Fedro A. Peccatori, F. Penault-Llorca, M.J. Piccart, Jean‐Yves Pierga, Hope S. Rugo, L. Shockney, G. Sledge, Sandra M. Swain, Christoph Thomssen, Andrew Tutt, Daniel Vorobiof, Binghe Xu, Larry Norton, E. Winer

Bibliographic record

VenueThe Breast · 2017
Typeerratum
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsBC Cancer Agency
FundersNational Cancer Institute
KeywordsMedicineBreast cancerRegretOncologyInternal medicineCancer

Abstract

fetched live from OpenAlex

The authors regret to misspell Dr F. Penault-Llorca's family name. The authors would like to apologise for any inconvenience caused. 3rd ESO–ESMO international consensus guidelines for Advanced Breast Cancer (ABC 3)The BreastVol. 31PreviewAdvanced Breast Cancer (ABC) comprises both locally advanced (LABC) and metastatic breast cancer (MBC) [1]. Although treatable, it is remains an incurable disease with a median overall survival of ∼2–3 years and a 5-year survival of only ∼25% [2–4]. Some more recent series seem to indicate an improvement in median overall survival [5,6]. Full-Text PDF

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)0.002
metaresearch head score (Gemma)0.040
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: Other · Consensus signal: none
Teacher disagreement score0.238
Threshold uncertainty score0.797

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.2380.173

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 head0.084
GPT teacher head0.378
Teacher spread0.295 · 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
GenreOther

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

Citations16
Published2017
Admission routes1
Has abstractyes

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