IC‐P‐124: VALIDATION OF THE EADC‐ADNI HARMONIZED PROTOCOL FOR MANUAL HIPPOCAMPAL SEGMENTATION
Bibliographic record
Abstract
An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. Aim of this study is to study the concurrent validity of the HarP towards local protocols, and its major sources of variance. 14 tracers segmented 10 ADNI cases scanned at 1.5T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and re-segmented following the HarP. The 5 most accurate tracers followed the HarP to segment 15 ADNI cases acquired at 3 time points on both 1.5T and 3T. The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89) (Figure). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) were very high. The volume variance due to different tracers was 0.9% of the total, comparing favourably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), and field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, p<0.001), and physiological variability (49.2%, p<0.001). The coefficient of variation due to tracer was very low (2.4%) (Table). Phase I: summary measures of the stability of the local and harmonized protocols among 14 naive tracers (inter-rater ICC based on both absolute and consistency methods). ICC: intraclass correlation coefficient C.I.: confidence interval. Comparisons of homologous absolute ICCs between local and harmonized protocols are significant on t-test at p<0.01.
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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 | 0.182 | 0.150 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".