Bibliographic record
Abstract
If your speaking is preventing you from getting the score you need in IELTS, Collins Speaking for IELTS can help. Don't let one skill hold you back. Collins Speaking for IELTS has been specially created for learners of English who plan to take the IELTS exam to demonstrate that they have the required ability to communicate effectively in English, either at work or at university. It is ideal for learners with band score 5 - 5.5 who are aiming for band score 6 or higher on the IELTS test (CEF level B1 and above). What is IELTS? The International English Language Testing System (IELTS) is sat by over 1.4 million candidates around the world every year. It is the most common test used by universities for foreign students to prove their language level. IELTS is also increasingly used for immigration purposes, with Australia, New Zealand and Canada all requiring visa applicants whose first language is not English to submit an IELTS grade. The system tests candidates' Reading, Writing, Listening and Speaking in four separate papers. Usually, students must gain a good mark in all four skills in order to gain entry to the course, job, or country of their choice. For this reason, candidates will often sit the exam numerous times to secure the score that they need. Powered by COBUILD The 4-billion-word Collins corpus is the world's largest database of the English language. It is updated every month and has been at the heart of Collins COBUILD for over 20 years.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.629 | 0.660 |
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".