Inter- and Intra-Observer Variations in Radiographic Evaluation of Pelvic Limbs in Yorkshire Terriers with Cranial Cruciate Ligament Rupture and Patellar Luxation
Bibliographic record
Abstract
The main aims of the study were to describe bone alignment differences in Yorkshire Terriers (YT) with cranial cruciate ligament rupture (CCLR), patellar luxation (PL), or with a combination of both (CCLR + PL); to verify the theory of increased strain on cranial cruciate ligament (CrCL) due to PL as a predisposing factor; and to evaluate intra- and inter-observer variability of the protocols developed for measurement of femoral and tibial alignment in Yorkshire Terriers. Fifty-five hindlimbs of YT were divided into four groups: Control, CCLR, PL, and CCLR + PL. Thirty parameters were radiographically evaluated including hip joint, femoral, tibial, and intercondylar fossa (ICF) parameters. Three observers evaluated all parameters on two separate occasions with a twelve-week interval between measurements. Significant differences in conjunction with CCLR and PL theories between groups were noticed in: Norberg angle (NA), quadriceps angle (Qa), anatomic lateral distal femoral angle (aLDFA), femoral varus (FVA), mechanical cranial proximal tibial angle (mCrPTA), mechanical caudal proximal tibial angle (mCdPTA), tibial plateau angle (TPA), distal tibial axis/proximal tibial axis angle (DPA). Some interesting findings are the similarity of values between Control and CCLR vs. CCLR + PL and PL groups in Na, Qa, aLDFA; between CCLR + PL and PL in FVA and a significantly lower age of dogs in CCLR + PL compared to CCLR group. Based on our results, we can conclude that YT with different clinical findings have differing bone morphology. Moreover, these findings may support PL as a predisposing factor for CCLR in small breeds. Measurements in which excellent inter- observer agreement was achieved may be used for surgical planning or for further discussions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".