Bibliographic record
Abstract
Use of fossil fuels in modern societies results in CO2 emissions which, together with other greenhouse gases in the atmosphere, increase environmental degradation and climate changes. Carbon dioxide emissions in a society are strongly related with energy consumption and economic growth, being influenced also from energy intensity, population growth, crude oil and CO2 prices as well as the composition of energy mix and the percentage of renewable energies in it.The last years in Greece, the severe economic crisis has affected all sectors of the economy, has reduced the available income of the citizens and has changed the consumers’ behavior including the consumption of energy in all the activities. Analysis of the available data in the region of Crete over the period 2007-2013 has shown a significant decrease of energy consumption and CO2 emissions due to energy use by 25.90% compared with the reduction of national G.D.P. per capita over the same period by 25.45% indicating the coupling of those emissions with the negative growth of the economy. Carbon dioxide emissions per capita in Crete in 2013 are estimated at 4.96 tons. Main contributors of those emissions in the same year were electricity generation from fuel and heating oil by 64.85%, heating sector by 3.23% and transportation by 31.92%.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".