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Record W4391985327 · doi:10.1016/j.ijscr.2024.109419

Undifferentiated carcinoma of the pancreas with osteoclast-like giant cells, a two cases report

2024· article· en· W4391985327 on OpenAlexafffund
Maria Luisa Tambasco, Philippe Echelard, Florence Perrault, Rabia Temmar, Vincent Quoc‐Huy Trinh, Yves Collin

Bibliographic record

VenueInternational Journal of Surgery Case Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsUniversité de Sherbrooke
FundersDepartment of SurgeryUniversité de Sherbrooke
KeywordsMedicineOsteoclastPancreasGiant cellPathologyCarcinomaCancer researchGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION AND IMPORTANCE: Fine needle aspiration is the standard method for the pathological evaluation of pancreatic masses. In the following context, rare variants of such masses might present a challenge. Our goal is to describe the clinical, cytological, and histological findings of two cases of undifferentiated carcinoma with osteoclast-like giant cells (UCOCGC) a rare variant of pancreatic ductal adenocarcinoma (PDAC). CASE PRESENTATION: Two cases were identified. Cytological findings exhibit similarities between the two cases. One patient received multiple chemotherapy regimens and a surgery and recurred within three years of diagnosis, while the other succumbed to cholangitis resulting from hepatic metastases a year after their initial surgery. DISCUSSION: UCOCGC is a rare variant of pancreatic cancer, characterized by a unique cytological aspect. Recognizing this variant is essential considering its distinct prognosis compared to usual pancreatic adenocarcinoma. CONCLUSION: We presented two cases of UCOCGC a rare pancreatic cancer variant, exposing diagnostic particularities and clinical evolution.

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)0.001
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.044
GPT teacher head0.334
Teacher spread0.291 · 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 designCase report
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

Citations3
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Surgery Case ReportsSame topicPancreatic and Hepatic Oncology ResearchFrench-language works237,207