Hoiho tracking: 21 January 2019 – 20 February 2019
Bibliographic record
Abstract
Another push to deploy GPS dive loggers on Yellow-eyed penguins from the Catlins was made in late January. The dire situation of breeding birds in the region turned out to be a major stumbling block for this endeavour as many of the nests intended for deployment at Hinahina Cove had failed so that only a single deployment was made on one of the last two remaining breeding females on 22 January 2019. Recovery of the device was attempted between 6pm and 11pm each day from 29 January and 5 February 2019. However, the penguin did not return on any of these days. On 30 January the two remaining nests at Hinahina Cove dissolved when all chicks – grossly underweight – were transferred to Dunedin for rehab. There is still hope that the device can be recovered when the bird returns to Hinahina Cove to moult. At Te Rere, on the 22 January 2019 a GPS dive logger and camera logger were deployed on the penguin that had exhibited linear foraging in December. Both its chicks are in good conditions and belong to the very small group of chicks not transferred to rehab. Recovery attempts began on 23 January 2019; the bird was recaptured, and devices were recovered on 25 January 2019. The bird had spent three days out at sea foraging in a region some 25 km from Te Rere consistently diving to 90-100m depths. The camera logger only yielded poor video data as the device’s lens cap leaked water which compromised image quality and destroyed the image sensor 35 minutes after recording had started. After these deployments it was decided to cease activities in the Catlins for the time being and instead focus on hoiho from the Otago Peninsula and Aramoana. On 11 and 12 February, two female hoiho were captured and fitted with a GPS dive logger at Cicely Beach (Otapahi). On 16 and 17 February, a total of five penguins were fitted with devices at Aramoana.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.108 | 0.058 |
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".