Examining intra- and inter-device reliability of pressure-mediated reflection spectroscopy in a multi-state sample of healthy adults
Bibliographic record
Abstract
Abstract Objective: To examine the intra- and inter-device reliability of devices using pressure-mediated reflection spectroscopy (the Veggie Meter®). Design: A cross-sectional research study was conducted across eight sites in the USA. Using two Veggie Meters® at each site, participants completed five, counter-balanced pairs of finger scans. Intra-device comparisons included intra-class correlation coefficients (ICC) and calculation of the CV and 95 % CI of each device/site; hypothesised to be ≤ 6 %. Inter-device comparisons included ICC, absolute relative differences (ARD) and 95 % CI, and equivalence; both hypothesised to be ≤ 10 %. Setting: Eight sites across the USA. Participants: Across sites, participants’ ( n 282) average age ranged 24·7–39·0 years; sex ranged 60·0–85·7 % women and Non-Hispanic White ranged 20·0–94·3 %. Results: Intra-device ICC ranged from 0·77 to 0·99. The CV ranged from 6·2 to 14·2 %, with an average of 8·8 %. A majority (63 %; n 10) of the Veggie Meter® devices had significantly higher CV from the hypothesised 6 %. Inter-device ICC ranged from 0·58 to 0·94. The ARD ranged from 7·5 to 22·0 %, with an average of 13·9 %. ARD in a majority ( n 5) of sites was significantly higher than the hypothesised 10 %. Five sites (63 %) demonstrated equivalence below the hypothesised 10 %. Conclusions: Our study demonstrates the intra-device and inter-device reliability to be moderate to high, as per ICC. The observed margin of difference within a device was up to 14 %, with an average of 9 %. The observed margin of difference between devices was up to 22 %, with an average of 14 % between devices.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".