Climate change and pandemics: New challenges for science and technology
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
Global warming is one of the major challenges that needsto be dealt with in the coming decades. In particular, theIntergovernmental Panel on Climate Change (IPCC) published a special report in 2018,[1] establishing the need fora limit to the global ambient temperature at the end of thepresent century (2100) of 2 C and, if possible, even 1.5 C,above the pre-industrial level. To attain these temperaturevalues, the United Nations asked all countries to presentNationally Determined Contributions (NDC), describingthe way how they would act to attain the upper limit of2 C; these include how to reduce greenhouse gases(GHG) and also to identify possible financial support formitigation and adaptation actions. However, scientificanalysis of the sum of the NDCs revealed less reductionthan needed, with final temperatures at 2100 in the rangeof 2.7?3.6 C.[2] Significant negative impacts, e.g., floodingin some regions and drought in others, glacier melting,food security concerns, disease vector propagation to highlatitude and altitude, ocean acidification, coral destruction,among others,[3] would occur on the whole planet if thelimits suggested by IPCC are not attained.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it