Three dimensional evaluation of posture in standing with the PosturePrint: an intra- and inter-examiner reliability study
Bibliographic record
Abstract
BACKGROUND: Few digitizers can measure the complexity of upright human postural displacements in six degrees of freedom of the head, rib cage, and pelvis. METHODS: In a University laboratory, three examiners performed delayed repeated postural measurements on forty subjects over two days. Three digital photographs (left lateral, AP, right lateral) of each of 40 volunteer participants were obtained, twice, by three examiners. Examiners placed 13 markers on the subjects before photography and chose 16 points on the photographic images. Using the PosturePrint internet computer system, head, rib cage, and pelvic postures were calculated as rotations (Rx, Ry, Rz) in degrees and translations (Tx, Tz) in millimeters. For reliability, two different types (liberal = ICC(3,1) & conservative = ICC(2,1)) of inter- and intra-examiner correlation coefficients (ICC) were calculated. Standard error of measurements (SEM) and mean absolute differences within and between observers' measurements were also determined. RESULTS: All of the "liberal" ICCs were in the excellent range (> 0.84). For the more "conservative" type ICCs, four Inter-examiner ICCs were in the interval (0.5-0.6), 10 ICCs were in the interval (0.61-0.74), and the remainder were greater than 0.75. SEMs were 2.7 degrees or less for all rotations and 5.9 mm or less for all translations. Mean absolute differences within examiners and between examiners were 3.5 degrees or less for all rotations and 8.4 mm or less for all translations. CONCLUSION: For the PosturePrint system, the combined inter-examiner and intra-examiner correlation coefficients were in the good (14/44) and excellent (30/44) ranges. SEMs and mean absolute differences within and between examiners' measurements were small. Thus, this posture digitizer is reliable for clinical use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".