Photo Quiz: Were those hyphae or pseudohyphae in blood culture?
Bibliographic record
Abstract
FIG 1Were those hyphae or pseudohyphae in blood culture?A previously healthy 55-year-old male construction worker was admitted to hospi tal with a new diagnosis of acute lymphoblastic leukemia (white blood cells 43.1 × 10*9 /L; neutrophils 2.16 × 10*9 /L; lymphocytes 15.52 × 10*9 /L; blasts 24.57× 10*9 /L).Three weeks prior to admission, he had intermittent fevers, dry cough, night sweats, nausea and vomiting, and 45-pound unintentional weight loss.Initially, he had unremarkable findings on chest computed tomography (CT) and blood culture (coagulase-negative Staphylococcus in one out of four bottles) but became neutropenic (white blood cells 13.9 × 10*9 /L; neutrophils 0.14 × 10*9 /L) on day 3 of admission, the day before he was started on the chemotherapy Hyper-CVAD Course A (cyclophosphamide, vincristine, doxorubicin, dexamethasone; for
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.177 | 0.027 |
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".