Studio anatomico di allineamento femorale nei cani di razza Labrador con metodica di ricostruzione tomografica
Bibliographic record
Abstract
RIASSUNTO OBIETTIVO: questo studio si propone di definire un protocollo all’avanguardia per misurare gli angoli femorali maggiormente alterati nei cani affetti da lussazione di rotula e definire i parametri fisiologici dei valori angolari per i cani di razza Labrador Retriever. MATERIALI E METODI: sono stati analizzati i femori di 10 cani (20 femori) di razza Labrador Retriever non affetti da patologie evidenti, di età compresa tra 12 e 14 mesi, tramite TC con scanner GE HiSpeed Multi Slice. I femori sono stati successivamente segmentati e ricostruiti con tecnica surface rendering tramite software di segmentazione semiautomatico elaborato da EndoCAS center, Università di Pisa, ed integrato nel software open source ITK-SNAP 1.5. Sono stati riprodotti posizionamenti frontali e assiali; le misurazioni angolari sono quindi state eseguite con il software OsiriX Lite® v.8.0.1 - 32 bit. RISULTATI: i valori misurati per l’aLDFA risultano in linea con la letteratura. Diversamente, l’A.I. e alcuni degli angoli misurati sul piano assiale si discostano dai valori riportati in letteratura, in quanto in questo studio alcune tecniche sono state riadattate, apportando accorgimenti volti a massimizzare la ripetibilità delle misurazioni e a minimizzare l’errore relativo tra operatori diversi. CONCLUSIONI: i risultati di questo studio costituiscono un database di intervalli fisiologici, al quale futuri studi su cani affetti da MPL potranno rifarsi. ABSTRACT OBJECTIVE: To define an innovative procedure to measure the most altered femoral angles in MPL affected dogs and to settle the standard physiological values for Labrador Retriever. MATERIALS AND METHODS: 20 femora form 10 healthy Labrador aged between 12 and 14 months have been studied using GE HiSpeed Multi Slice TC scanner. Femora have been segmented and 3D-reconstructed via surface rendering using a semi-automatic segmentation software developed by EndoCAS center, University of Pisa, integrated in the open source software ITK-SNAP 1.5. Frontal and axial positioning have been reproduced; the angular measurements have been then taken with OsiriX Lite® v.8.0.1 - 32 bit. RESULTS: Measured values for aLDFA are in line with literature. Differently the I.A. and some of the axial plane measured angles diverge from the quoted values found in literature, since in this study some techniques have been redefined, adding adaptations in order to maximize measurement repeatability and minimize interobserver error. CONCLUSIONS: The results of this analysis constitute a database of physiological ranges, to represent a reference for future examinations on MPL affected dogs.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".