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Record W2400033481 · doi:10.1177/1941874416651120

A Case Study in the History of Neurology

2016· article· en· W2400033481 on OpenAlexaff
Gregory S. Day, David F. Tang‐Wai, Michel Shamy

Bibliographic record

VenueThe Neurohospitalist · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeurology and Historical Studies
Canadian institutionsUniversity of OttawaUniversity of Toronto
Fundersnot available
KeywordsMedicineNeurologyClinical neurologyIntensive care medicinePsychiatryNeurosciencePsychology

Abstract

fetched live from OpenAlex

We review the case of a young man who developed a constellation of symptoms and signs-bizarre behavior, seizures, abnormal movements, and autonomic instability-that evaded diagnosis at the time of presentation. We use this case to explore the way medical knowledge changes over time. Despite the dramatic advances in our understanding of neurological diseases in recent decades, physicians tend to approach diseases and diagnoses as if they were immutable. Our case reinforces how the diagnosis and treatment of disease are determined by an ever-changing historical context driven by the rapid expansion of medical knowledge. We discuss the implications of this realization and present strategies for navigating the boundaries of knowledge, both in practice and in principle.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.061
GPT teacher head0.262
Teacher spread0.201 · 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 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

Citations5
Published2016
Admission routes1
Has abstractyes

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