Using agent-based modelling algorithms to analyze the impacts of toxic contaminations on Lake Ontario ecosystem
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent advances in computer technology have brought a revolution in ecological modelling. Ecoinformatics and computational ecology make use of various programs, including agent-based modeling algorithms, to study ecological systems. In this study, an in-silico analysis was performed using an agent based modelling software, to analyze the impacts of a potential toxin on Lake Ontario ecosystem. For easier duplication of the real world into the virtual system, the ecosystem was divided into 6 compartments. These compartments include phytoplankton, zooplankton, macroinvertebrates, forage fish, piscivores, and sea lamprey. The test model was performed under five different concentrations of toxin. Each test was repeated 15 times to reduce demographic stochasticity. The results suggest that toxic contaminations, such as mercury, could potentially lead to population reduction in forage fish, piscivores and sea lamprey compartments.Les progrès récents reliés à la technologie informatique ont amené une révolution dans la modélisation écologique. L’éco-informatique et l’écologie computationnelle utilisent plusieurs programmes, y compris des algorithmes basés sur les systèmes multiagents pour étudier les systèmes écologiques. Dans cette étude, une analyse insilico a été accomplie en utilisant les systèmes multiagents pour analyser les impacts d’une toxine potentielle dans l’écosystème du Lac Ontario. Afin de mieux améliorer la représentation du monde réel dans le système virtuel, l’écosystème du Lac d’Ontario a été divisé en six compartiments. Ces compartiments comprennent le phytoplancton, le zooplancton, les macroinvertébrés, les poissons fourragers, les piscivores et la lamproie marine. Ce modèle a été examiné sous cinq concentrations des toxines différentes. Chaque examen a été répété 15 fois pour réduire la stochasticité démographique. Les résultats suggèrent que des contaminations toxiques, comme la contamination par le mercure, pourraient potentiellement arriver à une réduction de la population des poissons fourragers, des piscivores et des compartiments de la lamproie marine.
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.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it