European School for Interdisciplinary Tinnitus (ESIT): A global research training initiative
Bibliographic record
Abstract
The European School for Interdisciplinary Tinnitus Research (ESIT) is an EU-funded doctoral training network. ESIT is a consortium of 12 universities, over 30 commercial and not‐for‐profit organizations, and 15 PhD students providing cutting-edge education across 10 European countries to develop highly knowledgeable and innovative experts in the field of tinnitus research. The ESIT consortium is composed of multidisciplinary researchers and academics engaged in supervising culturally diverse students from nine countries. Over the span of 4 years, ESIT students demonstrated transformational growth in academic and personal spheres and overcame multiple challenges. This case study documents the meaningful partnerships developed between students and the ESIT support network and some of the challenges faced by ESIT in training 15 international students during a global pandemic. It documents the co-creation of knowledge achieved by those engaged in a global shared learning journey and the conflicts and cultural dimensions that they navigated.
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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 | 0.018 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".