Bibliographic record
Abstract
Antarctic work is complicated by the factors that make it especially compelling for biological study: extreme seasonality, remote location, and freezing temperatures. Within this environment, penguins represent a major meso-predator and sentinel species. Gentoo penguins (Pygoscelis papua) span much of the Scotia arc from the Falkland Islands/Malvinas to continental Antarctica and overlap a wide array of gradients in terms of prey and environment. Examining their relationships with other key species, whether prey, parasite, or key primary producer, is a crucial way of understanding the broader biogeographical interactions within the Scotia Arc. In this thesis, I examine several key aspects of penguin biogeography in the Scotia Arc. First, I investigate the segregation of faecal microbiomes across geography and examine their connections with diet. Then, I use faecal samples to detect potential tapeworm infections in individuals and determine the relationship with bacterial microbiome and diet in those individuals. Next, all of this information is further studied with regards to the algal signatures present in gentoo faeces and the relation of them to other biogeographical factors. Finally, I consider the findings of these chapters within the broader context of extant work on the ecology of the Scotia Arc and for gentoo penguins specifically and lay out further areas for study.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".