Inter‐ and intraobserver agreement for CT measurement of mandibular and medial retropharyngeal lymph nodes is excellent in dogs with histologically confirmed oral melanoma
Bibliographic record
Abstract
Mandibular and medial retropharyngeal lymph nodes are routinely evaluated with CT when staging dogs with oral melanomas. While size alone is considered inadequate for detecting nodal metastasis, it is critical in evaluating treatment response, as clinical decisions are based on changes in size. It is common for different radiologists to measure the size of pre- and posttreatment lymph nodes in the same patient. The objective of this retrospective, observer agreement study was to evaluate the inter- and intraobserver agreement in measuring canine mandibular and medial retropharyngeal lymph nodes by a diverse population of veterinary radiologists and trainees. Fourteen dogs with documented oral melanoma and head CT studies identified from records of a single institution were included in this study. North American veterinary radiologists and trainees were recruited to measure the mandibular and medial retropharyngeal lymph nodes; in triplicate. Prior to performing the study measurements, participants completed a training tool demonstrating the lymph node measurements. Overall, interobserver intraclass correlation coefficient (ICC) was 0.961 (95% confidence interval [CI]: 0.946, 0.972) and intraobserver ICC was 0.977 (95% CI: 0.968, 0.983), indicating excellent agreement (ICC > 0.9 considered excellent). Similar findings were noted following sub-analysis for most variables (experience, size, laterality, axis of measurement). These results suggest that follow-up measurement of the long and short axis of the mandibular lymph nodes and short axis of the medial retropharyngeal lymph nodes in the transverse plane, performed by different veterinary radiologists using the same method of measure, should have minimal impact on clinical decision making.
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 | 0.021 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".