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Record W2279628125 · doi:10.3332/ecancer.2015.553

Lessons from the first ecancer symposium on angiogenesis in gastric cancer

2015· article· en· W2279628125 on OpenAlexaff
Audrey Nailor, Elisabetta Dejana, Andrew R. Reynolds, Shonit Punwani, Giuseppe Curigliano, Francesco Bertolini, Manish A. Shah, Romano Danesi, Robert S. Kerbel, Gordon McVie

Bibliographic record

Venueecancermedicalscience · 2015
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsUniversity of Toronto
FundersNational Institute for Health and Care Research
KeywordsMedicineAngiogenesisCancerClinical OncologyRelevance (law)OncologyCancer researchInternal medicinePolitical science

Abstract

fetched live from OpenAlex

In March 2015, ecancer hosted a symposium at the European Institute of Oncology in Milan, Italy on the topic of angiogenesis in gastric cancer. During this meeting, leaders in the field focused on the latest research on the topic of angiogenesis in gastric cancer, delivering lectures combined with interactive question and answer (Q & A) sessions and a roundtable discussion with the meeting's chairs. Topics covered included biomarkers, imaging, and the current state of antiangiogenic drugs in gastric cancer. This report will provide an understanding of the relevance of angiogenesis in gastric cancer research, and clinical experiences from diverse perspectives.

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)0.015
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0050.014
Insufficient payload (model declined to judge)0.0050.001

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 head0.046
GPT teacher head0.323
Teacher spread0.277 · 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
GenreCommentary

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
Published2015
Admission routes1
Has abstractyes

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