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Record W4384120368 · doi:10.1002/ajmg.b.32953

Ryssia Wolfsohn's 1907 dissertation on “the heredity of dementia praecox”

2023· article· en· W4384120368 on OpenAlexaff
Kenneth S. Kendler, Astrid Klee

Bibliographic record

VenueAmerican Journal of Medical Genetics Part B Neuropsychiatric Genetics · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDementia praecoxHeredityProbandInsanityPsychiatryDementiaGrandparentMental illnessPsychologyPsychopathologyMedicineSchizophrenia (object-oriented programming)Mental healthDevelopmental psychologyGenetics

Abstract

fetched live from OpenAlex

In the 19th century, psychiatric genetic studies typically utilized a generic category of "insanity." This began to change after 1899, with the publication of Kraepelin's 6th edition containing, among other disorders, his mature concept of dementia praecox (DP). We here review an article published by Ryssia Wolfsohn in 1907 from her dissertation at the University of Zurich entitled "Die Heredität bei Dementia praecox" (The Heredity of Dementia Praecox). This work, performed under the supervision of E. Bleuler, was to our knowledge the first formal genetic study of the then new diagnosis of DP. She investigated 550 DP probands admitted to the Burghölzli hospital with known information about their "heredity burden." For most probands, she had information on parents, siblings, grandparents, and aunts/uncles. Of these patients, only 10% had no psychiatric illness in their families. In the remaining probands, she found rates of the four major categories of psychopathology she investigated: mental illness-56%, nervous disorders-19%, peculiar personalities 12% and alcoholism 13%. Her most novel analyses compared either total familial burden or burden of her four forms of mental disorders on her DP probands divided by subtype and outcome. In neither of these analyses, did she find significant differences.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.307
Teacher spread0.265 · 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.

Study designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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