Феномен дискурсу у світлі антропоцентричної лінгвістики
Bibliographic record
Abstract
Check., Art.Fashion.Luxury goods.Antiques.Music.Technology gadgets There's nothing you can't buy in Madrid. , ' : BA's evolution into an ever more innovative, creative and modern city is a central priority for the City Government., A taste of BA culinary culture., Did you know that you can go to the Boston Museum of Fine Arts free on Wednesday nights?, Get kitted out for your Hong Kong trip with everything from maps to apps! - : ) -Don't miss: February Events, Don't expect to find too many bargains in Rome, Don't miss these Toronto family day weekend events for a memorable family getaway., Don't Miss These Shopping Experiences in Sydney., Don't miss out on the best Berlin exhibitions!, Don't Cut the Noodles!Celebrating Chinese New Year in Toronto!; ) Why -Why visit Milan?, Why study in BA?, Why go Amsterdam?, Why stay in Toronto?, Why admire Brussels?, Why film in Toronto?, Why love Istanbul?What Go Tokyo?!, Why not spend a sleepless night indulging yourself in the bright lights and music beats of Beijing?, Why Love Beijing?; ) -First time in London?, Looking to be swept away?, Want to experience the Tokyo stylish traditional tea ceremony?, Looking for things to do in Toronto?, Love a secluded Sydney beach?, Love to shop in Beijing?, In Tallinn for a limited time?, Visiting Berlin in 2015?, Are you travelling to Berlin and want to maximise your experience?. , , .
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".