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Record W7135913728

Investitionskontrolle in der Krise: Löcher im Schutzschirm?

2022· other· de· W7135913728 on OpenAlexaff
Stefan Mayr, Oliver Prausmüller

Bibliographic record

VenueWU Research · 2022
Typeother
Languagede
Field
Topic
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsSet (abstract data type)Work (physics)Term (time)
DOInot available

Abstract

fetched live from OpenAlex

Wer kauft sich da eigentlich ein? Diese Frage stellt sich nicht nur ganz aktuell beim Flughafen Wien. Mitten in der Covid-19-Krise machte etwa die mögliche Übernahme deutscher Impfstoffhersteller die deutsche Regierung hellhörig. Und schon davor hatte der Einkauf chinesischer Investor:innen in den strategisch wichtigen Hafen von Piräus ein Umdenken in Brüssel angestoßen.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.087
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0100.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0870.018

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 head0.144
GPT teacher head0.438
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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