Validity and Reliability of a Novel Handheld Osmolarity System for Measurement of a National Institute of Standards Traceable Solution
Bibliographic record
Abstract
PURPOSE: To evaluate the validity and reliability of a novel handheld osmolarity system (I-PEN Osmolarity System; I-MED Pharma Inc, Dollard-des-Ormeaux, Quebec, Canada) for measurement of the osmolarity of a National Institute of Standards and Technology (NIST) traceable solution at a variety of ambient temperatures. METHODS: A total of 65 measurements of an NIST solution with a verified osmolarity of 290 ± 2 mOsmol/L were taken using 3 separate handheld osmolarity systems, 65 unique single-use sensors (SUSs) from 3 different lots, and 2 adaptors. Mean values were calculated using the device, SUS, and adaptor. Measurements were taken using a handheld osmolarity system, an adaptor, and 56 individual SUSs at 6 different ambient temperatures ranging from 17.7 to 26.5°C. RESULTS: Overall, the mean osmolarity measured was 294.06 mOsmol/L (SD ±2.29; percent coefficient of variation 0.78), ranging from 286.60 to 298.18 mOsmol/L. This fell within a prespecified acceptable variability of ±4 mOsmol/L (SD ±7). Mean values did not vary across devices, adaptors, or single-use sensors used. Mean osmolarity measurements increased with rising ambient temperatures, with an R = 0.88. The temperature correction factor was calculated to be 2.01 mOsmol/L per °C. CONCLUSIONS: The osmolarity system reliably and accurately measured the osmolarity of an NIST solution in a laboratory setting, using an adaptor to correct for differences in resistance between a laboratory NIST solution measurement and direct measurements on the palpebral conjunctiva of the eyelid. The handheld osmolarity system represents a rapid and accurate instrument for measurement of tear osmolarity in a simulated testing setting.
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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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".