Additional file 6 of Efficient non-contrast enhanced 3D Cartesian cardiovascular magnetic resonance angiography of the thoracic aorta in 3 min
Bibliographic record
Abstract
Additional file 6: Figure S5. Bland–Altman plots for co-axial diameter measurements of mid aortic arch, mid descending aorta and distal descending aorta between the dNAV and the iNAV T2prep-bSSFP sequence for reviewer 2 (A, B, C) and reviewer 3 (D, E, F). Bland–Altman plots for co-axial diameter measurements of the mid aortic arch, mid descending aorta and distal descending aorta between the dNAV and the iNAV T2prep-bSSFP sequence for reviewer 2 (A, B, C) and reviewer 3 (D, E, F). The black line indicates the mean bias of the diameter measurements whereas the red lines represent the 95% confidence interval. Values are given in cm. A Good agreement with a mean difference 0.003 cm for reviewer 2 for the mid aortic arch (95% CI − 0.21 to 0.2) for reviewer 2; B good agreement with a mean difference of − 0.02 cm for reviewer 2 for the mid descending aorta (95% CI − 0.2 to 0.15); C good agreement with a mean difference of 0.03 cm for reviewer 2 for the distal descending aorta (95% CI − 0.13 to 0.2); D good agreement with a mean difference of 0.01 cm for reviewer 3 for the mid aortic arch arch (95% CI − 0.31 to 0.33); E good agreement with a mean difference of 0.006 cm for reviewer 3 for the mid descending aorta (95% CI − 0.25 to 0.29); F good agreement with a mean difference of − 0.02 cm for reviewer 3 for the distal descending aorta (95% CI − 0.25 to 0.2).
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 | 0.003 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.877 | 0.209 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".