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Record W2020647420 · doi:10.15273/dmj.vol28no1.4328

The Man Who Drank Too Much

2000· article· en· W2020647420 on OpenAlexaffvenue
Brian Le, Brian Nicholson

Bibliographic record

VenueDalhousie Medical Journal · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican Sports and Literature
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

A 35-year-old male presents with excessive thirst and urination of abrupt onset which he dates back to getting married 2 years ago.He awakens to drink and urinate 5 times nightly.There is no other significant medical or family history.Results on physical exam were unremarkable.Serum electrolytes, urea, creatinine, calcium, phosphate, and liver function tests were all within normal limits.Urine analysis revealed low specific gravity and osmolality, at 1.005 (Normal: > 1.015) and 190 mOsm/kg (Normal: 700 -1400 mOsm/kg) respectively (1).Ql: What would be your differential diagnosis for this patient?Q2: How would you distinguish amongst the polyuric syndromes? Hoffmann-La Roche LimitedTogether, with a strong Focus on the Future, cancer care will reach new levels.We know a brighter future for cancer patients and their physicians is within reach.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0130.003
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0060.015
Insufficient payload (model declined to judge)0.0390.013

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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2000
Admission routes2
Has abstractno

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Same venueDalhousie Medical JournalSame topicAmerican Sports and LiteratureFrench-language works237,207