Bibliographic record
Abstract
Ticks are obligate blood-feeding ectoparasites of many hosts, and are second only to mosquitoes as the most common arthropod pathogen vectors. Ticks use many different strategies to detect suitable hosts for a successful blood meal. They can actively search for hosts moving toward distant stimuli, or they wait on vegetation until a host comes within reach (aka. 'questing'). Through the questing process, ticks detect chemical stimuli associated with the host, relying on chemosensation. Olfactory information detected from a potential host will shape tick host-seeking behaviour, enhancing the likelihood of host contact. Other factors and cues linked to host detection include heat, detected through thermo-sensitive sensilla, humidity, detected through hygroreceptors, visual cues, detected through the optical system, and vibrations, detected through mechanoreceptors. The level of bacterial infection in ticks is also an important factor influencing host detection ability and tick behaviour. Here, an overview of the multiple factors shaping host detection in ticks is presented, unifying all the elements, and providing a comprehensive model coordinated by the multimodal tick sensory system.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.065 | 0.055 |
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".