Bibliographic record
Abstract
My bachelor’s thesis was a research on behaviour of selected feline predators and comparing the observed behaviour with a typical behaviour of individual animals in the wild and in captivity. In nature the feline predator’s behaviour is dominated by instincts which includes hunting, marking territory, social interactions and breeding strategies. Most of feline predators live solitary except of breeding season and raising offspring. On the other hand, in captivity these behaviours are affected by restricted territory, regular food supply and lack of natural stimulus. This can lead to change in behaviour like lack of hunting, increased predisposition to stereotypical or aggressive behaviour. Two wildlife and surveillance cameras were installed, and activities of cryophilic feline predators - Eurasian lynx (Lynx lynx) and Canada lynx (Lynx canadesis) and activities of thermophilic feline predators – Caracal (Caracal caracal) and Ocelot (Leopardus pardalis) were observed. Ethological observations were carried out from 02/2022 until 03/2023. The activities were recorded in weekly intervals. Based on the data collected it was possible to compare behaviours of wild animals with other research on behaviour of feline predators in captivity. Observing behaviour of the monitored animals it was confirmed that animals in captivity are mainly less active. Behaviour in captivity is clearly different from behaviour in the wild, where basic animal instincts are suppressed. I believe that understanding the behaviour of feline predators will help to their care in captivity as well as their protection in the wild.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".