Ectoparasites of hares (Lepus europaeus Pallas) in Konya Province, Turkey
Bibliographic record
Abstract
This study was conducted to detect ectoparasites of hares (Lepus europaeus Pallas) between the years of 2003 and 2015 in Konya Province, Turkey. In this period, 75 hares shot by hunters were examined for ectoparasites macroscopically. Ectoparasites detected on the hares were collected with pliers and stored in tubes containing 70% ethanol. The ticks were identified under a stereo zoom microscope. Other parasites were cleared in 10% KOH, rinsed in distilled water, and transferred to 70%, 80%, and 99% ethanol, respectively, and mounted on slides in Canada balsam. They were identified under a binocular light microscope. The results showed that 33 (44%) of the 75 hares were infested with a total of 309 ectoparasites. Four lice species (Phthiraptera), Haemodipsus lyriocephalus, H. setoni, H. leporis, and Menacanthus spp.; two flea species (Siphonaptera), Pulex irritans and Nosopsyllus fasciatus; three mite species, Cheyletiella parasitivorax, Dermanyssus gallinae, and Neotrombicula (N.) autumnalis; four ixodid tick genera, Ixodes, Haemaphysalis, Rhipicephalus, and Dermacentor; and one ixodid tick species, Haemaphysalis parva, were detected on the infested hares. In addition to these, thirteen ixodid and two argasid tick larvae were found on the hares.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".