It-Technologies In The Implementation Of Climate Projects
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
The global market for carbon units began to take shape during the first period of the Kyoto Protocol (2008–2012). In 2015, a new global climate treaty, the Paris Agreement, was approved, the economic mechanisms of which are still being developed. So far, a number of regional schemes operate in the world, including in the EU, a number of provinces in China, a number of US states and Canada (usually in the form of quota systems and carbon markets), and voluntary schemes. The article discusses IT technologies in the implementation of climate projects. Modern digital technologies are developing very quickly and are present in all business sectors. It is IT that helps companies to make the transition to a model of advanced harmless production, which means the use of safe materials, intelligent systems, etc. The essence of the concept is a description of approaches to the implementation of projects to reduce greenhouse gas emissions or increase the absorption capacity of ecosystems by Russian companies. Information technology is a set of methods and means of purposefully changing any properties of information. Information technology in the field of management makes the highest demands on the "human factor", having a fundamental impact on the qualifications of the employee. Information technology is an important component of the process of using information resources..
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 | 0.002 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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