Global warming and life under the water
Bibliographic record
Abstract
With the development of society, people have already stepped into a fast-developing industrial age. The use of fossil fuels, coal and petroleum has become a main source of carbon dioxide emission, which is the key of global warming. Carbon dioxide, in recent years, is known as a greenhouse gas which has caused a rise in global temperature. There are many harmful effects global warming would bring to humans. Due to dramatic climate change, it is time to raise people’s awareness towards this ecological and social issue. The purpose of this research was to find whether global warming would have any impact on life under the water and how that can be used in future predictions. This research report looked at the water data for Ontario Lake, one of the freshwater lakes among the Great Lakes. The databases of daily water surface temperature, ice concentration, and concentration of chlorophyll absorbed in water have all proven that global warming did have great influence on lacustrine organisms. Also, according to the trend that was produced from the databases, a rough future trend was able to be produced. At the end, there are also some suggestions on what people can do to reduce environmental impact.
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) | 0.293 | 0.005 |
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; both teacher heads agree on what is shown here.
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".