Bibliographic record
Abstract
A 75-year-old retired farmer living in rural Saskatche-wan, presented with fever, night sweats, and fatigue for three weeks and a two-day history of bilateral calf pain and lower extremity weakness in August.He report-ed occasional shortness of breath, but denied cough, altered bowel habit, chills, rash, arthralgia, or headache.He had no recent travel history or sick contacts, though he did have contact with animals including sev-eral miniature horses and a pet rabbit on his farm, and frequent attendance at horse shows.In the weeks prior to his presentation he had been working on the farm cleaning out an old barn.There was a positive remote history of multiple tick bites.Past medical history included hypertension, benign prostatic hypertrophy, rheumatoid arthritis, chronic obstructive pulmonary disease, atrial fibrillation, diver-ticulosis, and granulomatosis with polyangiitis, which had been symptomatic in the past with scleritis and upper airway inflammation but had been quiescent re-cently.Patient was taking methotrexate 10mg/week.At his home hospital the patient's white blood cell count was 17.9×109/L (4.1-10.0)and temperature was 37.2°C, reaching a high of over 38°C.Urine and blood cultures were negative.He was treated empirically with gentamicin 540mg IV q24h and ceftriaxone 2gm q12h.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".