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Record W3047259654 · doi:10.1212/wnl.0000000000010475

Clinical Reasoning: A 73-year-old man with recurrent aphasia, headaches, and confusion

2020· article· en· W3047259654 on OpenAlexaff
Gauruv Bose, Tess Fitzpatrick, Vignan Yogendrakumar, Jocelyn Zwicker, Gerard H. Jansen

Bibliographic record

VenueNeurology · 2020
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsHeadachesMedicineAphasiaWeaknessHyperintensityAspirinCardiologyAnesthesiaPediatricsInternal medicineRadiologySurgeryMagnetic resonance imagingPsychiatry

Abstract

fetched live from OpenAlex

A 73-year-old man presented with sudden right-sided weakness, aphasia, and low-grade headache. Medical history was pertinent for obstructive sleep apnea, hypertension, diabetes, and dyslipidemia, for which he was appropriately treated, in addition to taking aspirin for primary prevention. Initial bloodwork, head CT, and vessel imaging were normal. MRI showed a nonenhancing, nonrestricting T2 hyperintensity in the left temporal lobe, in addition to multiple microhemorrhages (figure 1, A and B). Symptoms resolved within 24 hours and he was discharged on a second antiplatelet agent (clopidogrel). Three weeks later, a second episode of aphasia and right-sided weakness occurred, resolving within hours. He returned to the hospital the following day as symptoms recurred again. He had had been continually complaining of headaches, and his family had noted a gradual cognitive decline over the past month. Repeat bloodwork and erythrocyte sedimentation rate were normal. MRI demonstrated persistent microhemorrhages and superficial siderosis, worsening of the left temporal lobe subcortical changes, as well as diffuse leptomeningeal enhancement.

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)0.000
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 score0.396
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.037
GPT teacher head0.313
Teacher spread0.276 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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