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Animals Among Us: The Lives of Humans and Animals in Contemporary American Fiction edited by John Yunker

2015· article· en· W16956518 on OpenAlexaff
Ashley E. Reis

Bibliographic record

VenueThe Goose · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsEnvironmental ethicsHistoryPhilosophy

Abstract

fetched live from OpenAlex

Human herpes virus 8 (HHV8) was discovered in 1994 in the biopsy of a Kaposi's sarcoma in a patient with AIDS. Since then it has been identified in all variants of Kaposi's sarcoma and in another two rare disorders: multicentric Castleman's disease and primary body-cavity based lymphomas. The case discusses a 68 year old, HIV-negative male patient, presenting Kaposi's sarcoma for one year and being monitored by dermatology, who presented for weakness, anorexia and fever. On examination, he was found to have adenitis of the lymph nodes in his neck, underarm and groin. A biopsy on one of the swellings led to findings characteristic of multicentric plasma cell variant Castleman's disease. Blood tests for HHV8 and HIV were carried out, resulting positive and negative respectively (IgG anti-HHV8 positive, title 1/640, indirect immunofluorescence). PCR amplification showed HHV8 in peripheral blood. Patient received 8 cycles of CHOP and rituximab, leading to complete disappearance of the adenitis and general symptoms, with no worsening of his Kaposi's sarcoma. Patient remained in complete remission for 10 months after treatment. This paper discusses the case of a HIV-, HHV8+ patient, diagnosed with classic Kaposi's sarcoma, who developed multicentric plasma cell variant Castleman's disease. The coincidence of two or more HHV8-related illnesses in a HIV-negative patient has rarely been described in medical literature. Treatment with rituximab combined with CHOP chemotherapy was effective in this case, and no worsening of the patient's KS was observed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.156
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.331
Teacher spread0.281 · 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 teacher head, 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

Citations0
Published2015
Admission routes1
Has abstractyes

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