Validation of the i-STAT system for the analysis of blood parameters in fish
Bibliographic record
Abstract
Portable clinical analysers, such as the i-STAT system, are increasingly being used for blood analysis in animal ecology and physiology because of their portability and easy operation. Although originally conceived for clinical application and to replace robust but lengthy techniques, researchers have extended the use of the i-STAT system outside of humans and even to poikilothermic fish, with only limited validation. The present study analysed a range of blood parameters [pH, haematocrit (Hct), haemoglobin (Hb), HCO3 (-), partial pressure of CO2 (PCO2), partial pressure of O2 (PO2), Hb saturation (sO2) and Na(+) concentration] in a model teleost fish (rainbow trout, Oncorhynchus mykiss) using the i-STAT system (CG8+ cartridges) and established laboratory techniques. This methodological comparison was performed at two temperatures (10 and 20°C), two haematocrits (low and high) and three PCO2 levels (0.5, 1.0 and 1.5%). Our results indicate that pH was measured accurately with the i-STAT system over a physiological pH range and using the i-STAT temperature correction. Haematocrit was consistently underestimated by the i-STAT, while the measurements of Na(+), PCO2, HCO3 (-) and PO2 were variably inaccurate over the range of values typically found in fish. The algorithm that the i-STAT uses to calculate sO2 did not yield meaningful results on rainbow trout blood. Application of conversion factors to correct i-STAT measurements is not recommended, due to significant effects of temperature, Hct and PCO2 on the measurement errors and complex interactions may exist. In conclusion, the i-STAT system can easily generate fast results from rainbow trout whole blood, but many are inaccurate values.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".