Use of epidemiological tools in the evaluation of six empirical methods of pregnancy diagnosis in mares in Senegal: a pilot study
Bibliographic record
Abstract
Due to the long gestation period of 11 months on average and the rarity of twin births in this species, horse breeders are particularly interested in the early diagnosis of pregnancy in mares. Modern methods such as ultrasound are generally expensive and not easily accessible in rural areas. The level of electrification in the villages makes their use more complex. It is in this context that this pilot study was conducted in the Kebemer area in Senegal. The aim is to determine the sensitivity and specificity of each test. In this study, ultrasound was used as the reference test. Six empirical methods of pregnancy diagnosis were selected. These were the "flank hollow", "rump", "thoracic subcutaneous veins", "tail", "udder" and "drumstick" methods. 100 mares were selected after ultrasound and divided into two subgroups of 50 pregnant and 50 non-pregnant mares. The highest DOR value was obtained for the "tail" method, which was 28.8. This method also had the highest area under the curve when constructing the ROC curve, which was 83%, and detected 100% of pregnant mares from 3 months of gestation. This means that its overall sensitivity is 90% but reaches 100% [80 ;100] from 3 months of pregnancy. The "thoracic subcutaneous vein" method has also detected 100% [77 ;100] of mares at 2 and 3 months of pregnancy. La longue durée de gestation de 11 mois en moyenne chez la jument et la rareté des naissances gémellaires, font que les éleveurs de chevaux accordent un intérêt particulier au diagnostic précoce de la gestation chez la jument. Les méthodes modernes de diagnostic telles que l’échographie sont généralement onéreuses et peu accessibles aux éleveurs ruraux. Le niveau d’électrification faible dans les villages rend plus complexe leur utilisation. C’est dans ce contexte que cette étude pilote visant à évaluer les méthodes empiriques de diagnostic de gestation chez la jument a été réalisée dans la zone de Kébémer au Sénégal. Il s’agit de déterminer la sensibilité et la spécificité de chaque test. Six méthodes empiriques de diagnostic de gestation ont été sélectionnées. Il s’agit des méthodes du "creux du flanc", de la "croupe", des "veines sous-cutanées thoraciques", de la "queue", de la "mamelle" et du "pilon ". 100 juments ont été sélectionnées après échographie et réparties en deux sous-groupes composés de 50 juments gestantes et de 50 non gestantes. La valeur du diagnostic odds ratio (DOR) la plus élevée soit de 28,8 a été obtenue pour la méthode dite de la "queue". Cette méthode a également obtenu la surface sous la courbe la plus élevée lors de l’établissement de la courbe ROC qui est de 83 % et a permis de détecter 100 % [80 ;100] des juments gestantes à partir de 3 mois de gestation. La méthode dite des "veines sous-cutanées thoraciques" a également détecté 100 % [77 ;100] des juments dont la gestation est âgée de 2 et de 3 mois.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".