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Record W2024627391 · doi:10.1002/gps.1347

Is collectionism a diagnostic clue for Diogenes syndrome?

2005· article· en· W2024627391 on OpenAlexafffund
Manuel Montero‐Odasso, Marcelo Schapira, Gustavo Duque, Mariana Chercovsky, Lucas Fernández-Otero, Roberto Kaplan, Luis Alberto Cámera

Bibliographic record

VenueInternational Journal of Geriatric Psychiatry · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsMcGill University
FundersMcGill University
KeywordsNeglectPrimary careSocial withdrawalPsychiatryPsychologyMedicineGerontologyPediatricsFamily medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Diogenes syndrome (DS) is characterized by extreme self-neglect, domestic squalor, and social withdrawal. Despite having been described decades ago, it is still difficult to persue a correct diagnosis in primary care clinics. METHODS: This paper reports a case of an elderly man with extreme self neglect and an abnormal collecting pattern whose condition remained undetected for many years. His collectionism was manifested with a tendency to store items in an organized manner but without a clear purpose. CONCLUSION: The authors suggest that the presence of collectionism could be a helpful clue towards diagnosis of DS in similar cases.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
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 head0.015
GPT teacher head0.330
Teacher spread0.316 · 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 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

Citations28
Published2005
Admission routes2
Has abstractyes

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