An adolescent with suspected sepsis and disseminated intravascular coagulation
Bibliographic record
Abstract
A previously healthy 14-year-old boy presented to his local emergency department with a 1-day history of fever, emesis, and decreased level of consciousness. There was no history of preceding diarrhea, medication intake, substance abuse, hypertension, recurrent infections, malignancy, kidney disease, or an autoimmune disorder. Family history was noncontributory. On examination, he was hypotensive, tachycardic, confused, with mild icterus and a petechial rash. His blood work showed leukocytosis, thrombocytopenia, and hemolysis. Given the history of fever, rapid clinical decompensation and suggestive blood work findings, he was suspected to have septic shock and disseminated intravascular coagulation (DIC). Cultures were drawn and he was started on ceftriaxone, vancomycin, and acyclovir. Further clinical deterioration led to the transfer to paediatric intensive care at a tertiary care centre. Worsening consciousness and hemodynamic instability warranted invasive mechanical ventilation and inotropic support. His CT head was normal. Within 24 hours, he developed anuria and acute kidney injury, requiring continuous veno-venous hemodiafiltration (CVVHDF). The findings on admission blood work were persistent thrombocytopenia, hemolysis, deranged liver, pancreatic and cardiac markers, and mildly elevated INR and PTT (Table 1). The serum C3, C4, direct coombs test, ANA, anti-dsDNA, p-ANCA, and c-ANCA levels were normal.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".