Instrument Error Codes and Diagnostic Serendipity
Bibliographic record
Abstract
A 60-year-old female patient presented to a family physician with recent symptoms of fatigue, but no prior medical problems. During that initial visit, the physician ordered laboratory evaluations for anemia (complete blood count, iron, and vitamin B12), thyroid status, and renal function (Table 1). The ordered test results were not remarkable except for an unexplained mild anemia: hemoglobin 9.1 g/dL (91 g/L); hyponatremia: Na 127 mmol/L; and hypoalbuminemia: albumin 2.1 g/dL (21 g/L). View this table: Table 1. Selected results of laboratory testing performed after initial evaluation of the patient with age- and sex-dependent reference intervals.a Results for vitamin B12 could not be provided by the laboratory. During the analysis, a series of instrument error codes were observed by staff and the instrument stopped. The error codes were triggered after incubation of plasma with reagents for measurement of vitamin B12 on an E601 analyzer (Roche Diagnostics). The error codes appeared in the software and computer that operates the E601 analyzer and were recorded by the middleware (Cobas I.T. middleware 1.05.02) but was not communicated to the laboratory information system). The 4 error codes indicated a shortage of auxiliary reagent, an abnormal measuring cell condition, an abnormal sipper pipette movement, and a tip/cup pickup error. During investigation, staff observed that as an automated pipette …
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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 | 0.001 | 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 | 0.000 | 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".