THE ROLE OF ENVIRONMENTAL CHARACTERISTICS ON FISH
Bibliographic record
Abstract
Aquatic ecosystems are influenced by physical, chemical, and biological processes operating at multiple spatial scales, from landscape through microhabitats. Processes operating at the landscape level, such as watershed land use or precipitation, are external factors that influence an aquatic ecosystem. Internal factors are processes operating on an aquatic ecosystem from within the system, such as habitat. I explored how external and internal factors influenced fish community structure and function in Lake Ontario embayments. With my research, I aimed to address the following questions: (1) which internal and external factors influence how much and where biomass is distributed in the fish community (i.e., structure); (2) which factors influence energy sources utilized by the fish communities (i.e., function); (3) are structural and functional responses related to each other? Structural characteristics responded to both external and internal factors. Biomass increased with phosphorus loading (external factor) and area (internal factor), whereas abundance increased and size structure decreased with percent vegetation (internal factor). Similarly, both external and internal factors influenced energy sources incorporated by the fish
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".