Bibliographic record
Abstract
How a leaf becomes a bird is an illustrative series by Dante Bresolin, one of our recently-completed undergraduate thesis students. While streams and forests are often treated as separate ecosystems, this series highlights the importance of forested streams for supporting several species at risk in Ontario, aquatic and terrestrial. In this series, Dante’s gifts are on full display: their macroinvertebrate expertise is paired with a love for birds, and incredible gift of illustrations that show us how these species are interconnected.\nMany insects (invertebrates) spend a portion of their life, typically the larval stage, in the aquatic stream environment. Leaf litter is an important source of energy for stream ecosystems, especially for foundational taxa such as aquatic macroinvertebrates. From scrapers to shredders, invertebrates have developed a range of feeding strategies to use leaf litter. The energy they gain fuels the base of the aquatic food webs, with many species relying on invertebrates for their own nutritional needs.\nWhen invertebrates eventually emerge from the waters as winged adults, they are preyed upon by several bird species. Aerial insectivores like chimney swifts and bank swallows feed on flying insects in the air, while warblers like the Louisiana waterthrush and Prothonotary warbler are known to nest and feed along rivers.\nThe forested streams and wetlands that these birds call home are threatened in Southern Ontario, and their continued destruction is a likely contributor the decline of aerial insectivores. Reflecting on how we can protect these species, and thinking beyond the stream, the story of how a leaf becomes a bird illustrates the critical role of conservation and restoration of freshwater habitats in protecting species at risk across Ontario.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.012 |
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".