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Record W3080548308 · doi:10.1016/j.ejso.2020.07.038

Combined liver resection and cytoreductive surgery with HIPEC for metastatic colorectal cancer: Results of a worldwide analysis of 565 patients from the Peritoneal Surface Oncology Group International (PSOGI)

2020· article· en· W3080548308 on OpenAlexaff
Réa Lo Dico, Matthieu Faron, Yutaka Yonemura, Olivier Gléhen, Marc Pocard, Armando Sardi, Martin Hübner, Dario Baratti, Gabriel Liberale, Alex Kartheuser, Ignace H. J. T. de Hingh, Paul H. Sugarbaker, Wim Ceelen, Brendan Moran, Manuela Robella, F. Quénet, Lucas Sidéris, Diane Goèré, Manuel Limbert, Paolo Sammartino, David L. Morris, J. Abba, K. Abboud, C. Arvieux, Sébastien Carrère, Olivier Facy, Gwénaël Ferron, G. Lorimier, Frédéric Marchal, Patrick Rat, J.‐J. Tuech, Laurent Villeneuve, Pablo Ortega‐Deballon

Bibliographic record

VenueEuropean Journal of Surgical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicIntraperitoneal and Appendiceal Malignancies
Canadian institutionsUniversité du Québec à MontréalHôpital Maisonneuve-Rosemont
FundersCentre hospitalier régional universitaire de LilleCentre Hospitalier Universitaire de NiceHospices Civils de Lyon
KeywordsMedicineColorectal cancerCytoreductive surgeryPeritoneal carcinomatosisOncologyOverall survivalGeneral surgeryInternal medicineResectionCancerSurgery

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.289
Teacher spread0.255 · 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 designObservational
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

Citations32
Published2020
Admission routes1
Has abstractno

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