„А вы в конец света верите?”. Апокалипсис в современной русской литературе: пророчества индейцев в романе Дмитрия Глуховского „Сумерки"
Bibliographic record
Abstract
Dmitry Glukhovsky’s Sumerki (Twilight, 2007) is the story of a young Muscovite \nwho takes up the task of decoding the prophecies of the Maya Indians and connects them with the catastrophes that plague today’s world: earthquakes in Iran, hurricanes in the USA, tsunamis in Indonesia, and drought and conflagrations in Russia. The newspaper headlines and TV news \nannouncements look like Maya Indian prophecies. While translating the old diary of a Spanish conquistador, he becomes involved in a maelstrom of incredible events which will help him interpret the predictions and look into the future, even at the cost of his own life. Can the world be saved? This is the question that Glukhovsky already asked his readers in his previous, dark and apocalyptic science fiction novel Metro 2033 (2005) about a bleak and not-too-distant future. His novel Sumerki is more than a novel – it is rather a metaphor and a manifesto.
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 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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.018 | 0.018 |
| Open science | 0.011 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.191 | 0.002 |
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; both teacher heads agree on what is shown here.
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".