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Record W6913188054 · doi:10.5282/edoc.34903

Repetitive negative thinking in adolescents and young adults

2025· dissertation· en· W6913188054 on OpenAlexfundno aff

Bibliographic record

VenueElectronic Theses of LMU Munich (Ludwig-Maximilians-Universität München) · 2025
Typedissertation
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaStudienstiftung des Deutschen VolkesMedical Research CouncilNational Institute for Health and Care Research
KeywordsYoung adultSample (material)Action (physics)Cognition

Abstract

fetched live from OpenAlex

DanksagungAn dieser Stelle möchte ich mich bei allen Menschen bedanken, die mich während meiner Promotionszeit begleitet haben und ohne deren Unterstützung dieses Dissertationsprojekt nicht möglich gewesen wäre.Zunächst möchte ich mich bei meinem Doktorvater, Prof. Dr. Thomas Ehring, für die großartige Betreuung meiner Promotion bedanken.Dein fachlich hervorragendes Feedback sowie Deine stets unterstützende Art und Dein großes Vertrauen in meine Vorhaben waren ausgesprochen motivierend für mich.Eine bessere Anleitung hätte ich mir für meine Ausbildung als Wissenschaftlerin nicht wünschen können, und ich danke Dir von Herzen!

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.278
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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