Bibliographic record
Abstract
Using the FTUK Coupon Code “OFF99” gives traders a real advantage before they even start trading. With this code, you immediately receive a 20% discount on your challenge fee, reducing your entry cost and letting you save more capital for future trades. This offer is perfect for traders who want to join a reliable prop firm without spending too much upfront. You’ll gain access to FTUK’s high-quality trading platform, generous profit splits, and fast payouts. The savings you get from the code can be used to upgrade your account size or take multiple challenges at once. By applying “OFF99,” you unlock the same powerful benefits as top-funded traders at a lower price. FTUK ensures that every trader, whether in the US, UK, Germany, Singapore, UAE, or Canada, can take full advantage of this exclusive deal. It’s not just a discount — it’s your first step toward professional funding and trading freedom. Don’t miss this chance to start your journey smarter and stronger with FTUK.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.724 | 0.528 |
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; the direct Gemma label and the distilled Codex classifier 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".