Additional file 1: of Community paramedic point of care testing: validity and usability of two commercially available devices
Bibliographic record
Abstract
Table S1. Summary of characteristics of the Abbott i-STAT® and Alere epoc®. Figure S1. Results for sodium from i-STAT and epoc compared to gold standard (‘Lab’ – Calgary Lab Services), and between i-STAT and epoc. All results reported in mmol/L. Figure S2. Results for potassium from i-STAT and epoc compared to gold standard (‘Lab’ – Calgary Lab Services), and between i-STAT and epoc. All results reported in mmol/L. Figure S3. Results for chloride from i-STAT and epoc compared to gold standard (‘Lab’ – Calgary Lab Services), and between i-STAT and epoc. All results reported in mmol/L. Figure S4. Results for creatinine from i-STAT and epoc compared to gold standard (‘Lab’ – Calgary Lab Services), and between i-STAT and epoc. All results reported in umol/L. Figure S5. Results for hematocrit from i-STAT and epoc compared to gold standard (‘Lab’ – Calgary Lab Services), and between i-STAT and epoc. All results reported in %. Figure S6. Results for hemoglobin from i-STAT and epoc compared to gold standard (‘Lab’ – Calgary Lab Services), and between i-STAT and epoc. All results reported in g/L. Figure S7. Results for glucose from i-STAT and epoc compared to gold standard (‘Lab’ – Calgary Lab Services), and between i-STAT and epoc. All results reported in mmol/L. Figure S7. Results for glucose from i-STAT and epoc compared to gold standard (‘Lab’ – Calgary Lab Services), and between i-STAT and epoc. All results reported in mmol/L. (DOCX 773 kb)
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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 | 0.000 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.957 | 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".