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Record W4280626730 · doi:10.15173/ijsap.v6i1.4877

European School for Interdisciplinary Tinnitus (ESIT): A global research training initiative

2022· article· en· W4280626730 on OpenAlexvenueno aff
Giriraj Singh Shekhawat, Stuart Schonell, Stefan Schoisswohl, Roshni Biswas, Axel Schiller, Winfried Schlee

Bibliographic record

VenueInternational Journal for Students as Partners · 2022
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsCultural competencePsychologyMedical educationPedagogyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0030.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.305
GPT teacher head0.624
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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