Ambiente e Salute News n.19 - gennaio-febbraio 2023
Bibliographic record
Abstract
The recent release (March 2023) of the sixth report on climate change by the Intergovernmental Panel on Climate Change (IPCC) presents a comprehensive assessment of the current state of knowledge on the observed impacts and projected risks of climate change. It confirms the strong interactions of natural, social and climate systems and the negative impacts on both nature and people caused by human-induced climate change. The most vulnerable people and systems are disproportionately affected, and climate extremes have led to irreversible impacts. Emphasis is placed on the importance of limiting global warming to 1.5° C if the goal of a just, equitable, and sustainable world is to be realized, and the urgency of taking more ambitious action by highlighting that if we act now, we can still ensure a sustainable and livable future for all. There are feasible and effective adaptation options that can reduce risks to nature and people, and greater ambition is needed in both adaptation and mitigation measures. Climate-resilient development in all human activities is therefore important, and this requires urgent and conscious attention from both policy makers and the general public. In this journal we continue to summarize briefly the main articles published in the monitored journals, including those related to climate change. All articles and editorials deemed worthy of attention are listed divided by topic, with a brief commentary. This issue is based on the systematic monitoring of publications in January and February 2023.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.338 | 0.263 |
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".