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Record W6982924765

Künstliche Intelligenz in Bibliotheken : 34. Österreichischer Bibliothekartag Graz 2019 / von Köstner, Christina / „Suizid-Bücher“ – Provenienzforschung und bibliothekarische
\nErinnerungsarbeit

2020· article· de· W6982924765 on OpenAlexaff

Bibliographic record

VenueUnipub UB Graz (Universität Graz) · 2020
Typearticle
Languagede
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsBibliothèque et Archives nationales du Québec
Fundersnot available
KeywordsContext (archaeology)PersecutionJudaism
DOInot available

Abstract

fetched live from OpenAlex

This contribution addresses the topic of suicide, an issue only marginally discussed in the context of provenance research.The humiliation, discrimination, dispossession, and persecution under the NS regime led to an increase of suicides among Jewish people.First, the source material available in Austria is described through examples.The case study of Eleonora

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Bibliometrics, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0180.067
Science and technology studies0.0020.002
Scholarly communication0.0010.006
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.040
GPT teacher head0.287
Teacher spread0.246 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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