A comparison between measured female linear arm strengths and estimates from the 3D Static Strength Prediction Program (3DSSPP)
Bibliographic record
Abstract
This study performed a direct comparison between empirically measured female linear arm strengths and those estimated with the 3D Static Strength Prediction Program (3DSSPP). Linear arm strengths were collected from 15 female participants, at four hand locations and six primary directions (n = 360), and then estimated with 3DSSPP incorporating each participant's own segment lengths, body masses and joint strengths, and the measured arm postures from each trial to optimize the accuracy of 3DSSPP. In spite of this, the errors in 3DSSPP's estimated arm strength values were very high (RMS error = 56.0 N and 40.4%) and poorly correlated (r2 = 29.2%) with measured strengths. These results seriously question the accuracy of 3DSSPP to estimate female linear arm strengths and percent capable values, for the range of conditions tested, likely due to the overly simplified assumptions made to estimate triaxial shoulder strength.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".