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Record W2766774489 · doi:10.3747/co.24.3592

A Case of Metastatic Prostate Cancer and Immune Thrombocytopenia

2017· article· en· W2766774489 on OpenAlexaffvenue
Devin Betsch, Samantha Gray, Seif El Din Abo Zed

Bibliographic record

VenueCurrent Oncology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsSaint John Regional HospitalDalhousie University
Fundersnot available
KeywordsMedicineProstate cancerMalignancyBone marrowProstateCancerImmune thrombocytopeniaBone marrow failureImmune systemOncologyInternal medicinePathologyImmunologyPlateletHaematopoiesis

Abstract

fetched live from OpenAlex

Prostate cancer frequently metastasizes to bone, but bone marrow involvement is relatively less common. In advanced prostate cancer, significant bone marrow infiltration can result in hematologic abnormalities such as anemia and thrombocytopenia. We report the case of a patient who presented with a new diagnosis of thrombocytopenia at the same time that he presented with prostate cancer metastatic to bone. He was found to have immune thrombocytopenia (itp) which responded to treatment with steroids. We discuss this case and review the literature on itp in the setting of advanced malignancy.

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)0.005
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 score0.008
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0040.002
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.073
GPT teacher head0.413
Teacher spread0.340 · 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

Citations9
Published2017
Admission routes2
Has abstractyes

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