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
Record temperatures across most of the world in 2023 also affected water resources and water-related hazards. Heatwaves contributed to deepening and new droughts in South America and Canada. There were many extreme rainfall events, including several cyclones. The global water cycle in 2023 was influenced by a change in circulation and ocean water temperatures in the Pacific Ocean from La Niña to El Niño conditions but against a backdrop of overall increasing sea surface temperatures due to global warming. The higher temperatures increase the strength and rainfall intensity associated with storm systems such as tropical cyclones. There were a relatively large number of such events in 2023, and the human and economic toll was large. The year started with continuing heavy rain and flooding in the Philippines and the western USA. In February, cyclonic storm systems hit Madagascar, Malawi and Mozambique in southeast Africa, while heavy rain caused floods and landslides in southeastern Brazil. In April, southeast Asia was hit by a large-scale heatwave, followed by cyclone Mocha in Myanmar. The first half of the year also saw extremely dry conditions in northern Argentina and nearby regions and in southwestern Europe. In May, record dry conditions in northern Italy were abruptly ended by heavy rainfall and flooding. An extremely wet season in South Korea, India and Pakistan brought landslides and flooding between June and August, while in Canada, very dry and hot conditions caused a record wildfire activity. From July onwards, very dry and recurrent hot conditions across South America led to a rapidly developing drought in the Amazon basin that intensified during the second half of the year. In September, a Mediterranean cyclone or ‘medicane’ brought heavy rainfall to Greece and caused reservoir dams to fail in Libya, killing thousands. In November, several years of deepening drought in Somalia were interrupted by heavy rainfall and flooding, while nearby South Sudan largely remains in drought. The final weeks of 2023 brought severe storm systems with heavy rains and flooding to the northeast coast of Australia. At the start of 2024, the greatest risk of developing or intensifying drought appears to be in Central and South America (except southern Brazil and Uruguay), southern Africa and western Australia. Regions unlikely to develop drought for at least several months include the Sahel region and the Horn of Africa, northern Europe, India, China and southeast Asia, and southern Brazil and Uruguay.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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