Bibliographic record
Abstract
Faced with the challenges that climate change poses to all human societies, adaptation is becoming a necessity for human survival. In this context, it is necessary to study the climatic phenomena that humans face and that are likely to impact various aspects of life. Therefore, this study sought to analyze the trend of heat waves in Senegal using data from the Coupled Model Intercomparison Project Phase 6 (CMIP6), Canadian Earth System Model Version 5. Three climate scenarios (Shared Socioeconomic Pathway [SSP]1-2.6, SSP2-4.5, and SSP5-8.5) were used, and the study focused on two future climate normals (2020 – 2050, 2050 – 2080). The study first spatialized the 95th percentile of minimum, mean, and maximum temperatures, then analyzed temperature anomalies with the Lamb index before studying the future trend using the Mann-Kendall test. The results obtained reflect an upward trend for all the variables in this study for the two periods combined but with a different level of significance. This increase is greater for minimum temperatures, with rises of 0.43°C for SS1-2.6, 1.06°C for SSP2-4.5, and 2.18°C for SSP5-8.5. In comparison, maximum temperatures rose by 0.50°C, 1.05°C, and 2.03°C, respectively, between the first and second periods. Mean temperatures followed the same dynamic, with 0.48°C for SSP1-2.6, 1.04°C for SSP2-4.5, and 2.16°C for SSP5-8.5. Given these findings, it is important to analyze the behavior of the other CMIP6 models in assessing heat waves in Senegal.
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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".