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Record W2915844014 · doi:10.14740/gr1141

Malignant Peritoneal Mesothelioma Without Asbestos Exposure

2019· article· en· W2915844014 on OpenAlexvenueno aff
Hafsa Abbas, Julio C. Rodríguez, Hassan Tariq, Masooma Niazi, Ahmed Alemam, Suresh Kumar Nayudu

Bibliographic record

VenueGastroenterology Research · 2019
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsnot available
Fundersnot available
KeywordsAsbestosMesotheliomaMedicinePeritoneal mesotheliomaPathologyMetallurgyMaterials science

Abstract

fetched live from OpenAlex

Malignant mesothelioma is a rare neoplasm of the serosal linings. Mesothelioma has been linked to asbestos exposure, with prior asbestos exposure linked to 33-50% of malignant peritoneal mesotheliomas. We describe a case of malignant peritoneal mesothelioma (MPM) without any prior exposure to asbestos in a 40-year-old Hispanic female who presented to the emergency department with worsening abdominal pain and distension. She had a history of beta thalassemia trait and iron deficiency anemia. Examination revealed a distended abdomen with protruding umbilicus and positive shifting dullness. Laboratory tests showed anemia. Computed tomography (CT) of the abdomen revealed massive complex ascites suspicious of a malignant process. Ascitic fluid analysis showed serum ascites albumin gradient (SAAG) of 1.1 g/dL with a total protein of 5.2 g/dL. She underwent laparoscopic peritoneal biopsy which yielded epithelioid type malignant mesothelioma. She was started on chemotherapy with cisplatin and pemetrexed. The last follow-up was 27 months after the diagnosis. MPM is a rare and life-threatening malignancy. Frequently, the symptoms are non-specific. This poses a diagnostic challenge for physicians and probably the reason why the diagnosis is often delayed, especially in the absence of risk factors.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.032
GPT teacher head0.346
Teacher spread0.313 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2019
Admission routes1
Has abstractyes

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