Bibliographic record
Abstract
Bats aren't the only creatures that take refuge in caves. Some moth species make caves and abandoned mines their homes, even though the bat occupants may prey on them. James Fullard and an international team of colleagues from Canada, South Africa and Australia explain that one Australian noctuid moth,the granny's cloak moth (Speiredonia spectans), routinely shares its day roosts with bats (Miniopterus australis and Rhinolophus megaphyllus) that dine on insects. Fullard and his team suspected that the moths are able to evade the hungry bats because they hear the predator's echolocation calls, so they decided to test the insect's hearing(p.3808).First the team filmed the moths' and bats' activity in three abandoned Queensland mines to see how the moths respond to the predators and found that the insects avoid flying when the bats are airborne. Meanwhile the team rigged up ultrasound recording equipment and recorded and analysed the echolocation calls of three of the four bat species that occupied the mines.Having collected moths, the team returned to the lab and tested the insect's hearing by playing them echolocation call recordings and a range of sounds at various frequencies and volumes. They found that the moths have exquisitely sensitive hearing in the same frequency range as the echolocation calls of M. australis and R. megaphyllus. The insects could hear both bats' echolocation calls, but responded most strongly to R. megaphyllus. The team also found that the moths are deaf to the majority of the extremely high frequency calls from Hipposideros ater, a bat that does not cohabit with the insect, although the insects can pick up some of the bat's lower frequencies but only when the predator is probably too close to escape.Having found that granny's cloak moth listens out for the bats it cohabits with, the team suggest that the moths protect themselves by lying low and remaining perched when the bats are about. But why doesn't the moth cohabit with H. ater, which it cannot hear? Surely the silence would make the cave an attractive place to rest? Not according to Fullard and his colleagues. They suspect that the moth's relative deafness to the bat's high frequency calls makes it extremely vulnerable, allowing the bat to wipe out hapless moths that blunder into their roosts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.005 | 0.001 |
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".