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Record W1982096336 · doi:10.1186/1756-0500-7-276

Recognizing Diogenes syndrome: a case report

2014· article· en· W1982096336 on OpenAlexaff
Jeffrey DC Irvine, Kingsley Ezechinyere Nwachukwu

Bibliographic record

VenueBMC Research Notes · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsSaskatchewan HospitalUniversity of Saskatchewan
Fundersnot available
KeywordsShameHoarding (animal behavior)NeglectMedicinePersonal hygienePublic healthPsychiatryPsychologyFamily medicineNursingFeeding behavior

Abstract

fetched live from OpenAlex

BACKGROUND: Diogenes syndrome is a behavioural disorder characterized by domestic squalor, extreme self-neglect, hoarding, and lack of shame regarding one's living condition. Patients may present due to a range of reasons. Recognizing these will allow for earlier management of this high-mortality condition. CASE PRESENTATION: 61-year Caucasian female known with bipolar 1 disorder presented with manic symptoms. She was very unkempt and foul smelling. After being admitted involuntarily, she requested that someone go to her home to feed her pets. Her house was filled with garbage, rotting food, and animal feces. She had no insight into any personal hygiene or public health problems. CONCLUSIONS: Patients with Diogenes syndrome may be difficult to identify. Knowledge of the characteristics of Diogenes syndrome can aid in earlier recognition of such individuals, in order to decrease morbidity and mortality, and to improve public health.

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)0.000
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0050.002
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0060.005
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 head0.319
GPT teacher head0.483
Teacher spread0.164 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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