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Record W6940292030 · doi:10.7479/ws8v-z270/12

Was Füchse im Museum suchen | What foxes are looking for in the museum

2022· dataset· de· W6940292030 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMuseum für Naturkunde Berlin - Leibniz-Institut für Evolutions- und Biodiversitätsforschung · 2022
Typedataset
Languagede
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsMinnow Environmental (Canada)
Fundersnot available
KeywordsIdeal (ethics)

Abstract

fetched live from OpenAlex

In der Stadt einem Fuchs zu begegnen, ist keine Seltenheit. Ein Grund dafür ist, dass Städte viel grüner sind als man im ersten Moment denkt - so werden Stadtparks und Friedhöfe zum Rückzugsort für die Tiere. Warum diese Orte ideal sind und wie sich das Verhältnis von Mensch und Fuchs entwickelt hat, wird in diesem Artikel erzählt. Encountering a fox in the city is not uncommon. One reason for this is that cities are much greener than you might think at first glance - so city parks and cemeteries become a retreat for the animals. Why these places are ideal and how the relationship between humans and foxes has developed is told in this article.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), 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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.022
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.004
Science and technology studies0.0080.001
Scholarly communication0.0030.004
Open science0.0050.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0240.003

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 head0.023
GPT teacher head0.272
Teacher spread0.249 · 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