Bibliographic record
Abstract
Purpose : This research scholarship provide an individual with a grant to shape up and change the face of online gambling industry within the next few years Eligibility : 1. Full time student at college/university (preferred Marketing, Business or Communication courses). 2. No entry limit per contestant. 3. Casinomucho.com employees immediate families are not eligible. 4. 3,000–5,000 words essay on one of the given topic in Microsoft Word format with correct grammar, heading and punctuation. 5. The article must be plagiarism free Level of Study : Postgraduate Type : Scholarship Value : £500 Frequency : Annual Country of Study : United Kingdom Application Procedure : 1. Students must submit their applications to scholarship [at] muchoent.com . 2. Applications should include: full name, date of birth, name or degree course, essay in Word format Closing Date : 31 March Funding : Private Additional Information : casinomucho.com/scholarship/ For further information contact: Email :: scholarship@muchoent.com
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.184 | 0.047 |
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".