Bibliographic record
Abstract
An extremely distinguished British scientist, Professor Lord Rees, a former President of the Royal Society of London, said some 10 years ago "mankind has a 50/50 chance to survive the 21st century".I am not sure if, in the light of what is happening now, we should not revise that deadline and possibly shorten it.The perfect storm of world catastrophe is unfolding.In Europe we are slowly being engulfed in it all.For the last 20 years the Horn of Africa has experienced increasing poverty because of poor governance, constant civil wars, increasing drought, and finally large movements of people.For the last five years there has been a series of droughts in Ethiopia, Eritrea, Somalia, parts of Kenya.That drought has mean that there is less water, less food can grow, there is less for the animals of nomadic people to eat, less water for people in the cities to consume.The drought has spread all over the Middle East.Saudi Arabia a decade ago made it illegal to use water for irrigation; you can use water from local aquifers for human use only.This has encouraged the Saudis the Qataris, the Omanis, to invest in lands in other parts of the world, primarily in Africa.Even weaker people in those lands have been expropriated from their traditional lands.Now we have seen the emergence of ISIS.We are all concentrating on the fact that
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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.014 | 0.024 |
| Insufficient payload (model declined to judge) | 0.055 | 0.036 |
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".