Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The motion of a sprint canoe blade through the water is extrapolated from video analysis of the paddle handle motion and used to approximate the forces acting on the blade throughout a stroke. Frame analysis of the video provides the displacement of the blade, and consequently the water velocity and angle of attack at both the top and bottom of the blade. Based on a quasi-steady approach, the relative velocities and angles of attack are used to approximate the lift and drag forces acting on the blade, which are then decomposed into propulsive and vertical forces. Lift forces on the blade contribute significantly to both propulsive and vertical forces. The different flows and forces in the three phases of the stroke: catch, draw, and exit, can be seen. The end of the catch phase experiences large propulsive and small upward vertical forces. During the draw phase there is a strong propulsive force, with evidence of a double peak. The vertical force steadily declines and becomes negative as the horizontal angle becomes greater than 90°, and reaches large negative values at the end of the draw. During the exit phase both the propulsive and vertical forces approach zero.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 it