Bibliographic record
Abstract
A 37-year-old female with a history of acute intermittent porphyria (AIP) and hemochromatosis presented to the emergency department after experiencing intense abdominal and back pain with nausea. She was admitted to hematology and bloodwork was monitored periodically. Centrifugation of the lithium heparin samples revealed chocolate-colored plasma (Fig 1). However, chemistry results autoverified, without serum indices flags on Roche Cobas c503. Her urinary porphobilinogen/creatinine ratio was >34 µmol/mmol (reference interval <1.7 µmol/mmol). The patient’s lithium heparin plasma samples after centrifugation upon (A) admission, (B) 6 h post-treatment, (C) 24 h post-treatment, (D) 36 h post-treatment, (E) 48 h post-treatment, and (F) 72 h post-treatment. Color figure available at https://academic.oup.com/clinchem. Questions What investigations would be helpful in determining the cause of chocolate-colored plasma? What is the treatment for acute intermittent porphyria? Which assays would be affected by chocolate-colored plasma? The answers are below. Upon ruling out in vivo hemolysis and methemoglobinemia as common causes of brown plasma (1), chart review revealed that the patient was treated for the AIP flare with a hematin infusion. Hematin is brown in color and led to the discolored plasma at 6 h post-treatment (Fig 1B) and persisted at 72 h post-treatment (Fig 1F). Further investigations should be performed to determine whether hematin interferes with any spectrophotometric assays (2–4). The corresponding author takes full responsibility that all authors on this publication have met the following required criteria of eligibility for authorship: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; (c) final approval of the published article; and (d) agreement to be accountable for all aspects of the article thus ensuring that questions related to the accuracy or integrity of any part of the article are appropriately investigated and resolved. Nobody who qualifies for authorship has been omitted from the list. Janet Zhou (Conceptualization-Equal, Data curation-Equal, Formal analysis-Equal, Investigation-Equal, Methodology-Equal, Project administration-Equal, Validation-Equal, Visualization-Equal, Writing—original draft-Equal, Writing—review & editing-Equal), and Albert Tsui (Conceptualization-Equal, Formal analysis-Equal, Investigation-Equal, Methodology-Equal, Project administration-Equal, Supervision-Equal, Validation-Equal, Visualization-Equal, Writing—original draft-Equal, Writing—review & editing-Equal). Upon manuscript submission, all authors completed the author disclosure form. None declared. A.K.Y. Tsui has served on an advisory board for Novo Nordisk.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".