The science of climate change : what do we know?
Bibliographic record
Abstract
The natural process by which the earth is kept at a temperature making it a livable planet is the called the greenhouse effect. Credible scientific assessments on climate change have been made possible by the recording of increased atmospheric concentrations of greenhouse gases, the changes in the climate that were observed, and the experiments involving the modeling of climate change. Climate change has appeared as an issue on policy agendas as a result of these assessments. Increasingly advanced computer models have managed to successfully convince the scientific community that climate change will bring with it higher temperatures, more intense precipitation as well as magnified warming in countries at high latitudes, such as Canada, despite remaining uncertainties concerning how human activities will affect the climate. Response strategies cannot be refined until these uncertainties are reduced considerably. For example, in the case of extreme events, the spatial and temporal variations in climate change must be clearly understood before the response strategies are developed. refs., 2 tabs., 5 figs.
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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.012 | 0.030 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".