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Record W6921635155 · doi:10.7479/64y2-m311/75

Zoos und Artenschutz / Zoos and Conservation

2022· dataset· de· W6921635155 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
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsMinnow Environmental (Canada)
Fundersnot available
KeywordsNatural history

Abstract

fetched live from OpenAlex

Zoos bewerben sich heute als Artenschutzzentren. Bis in die 1970er Jahre wurde die Mehrzahl der ausgestellten Tiere allerdings in der Wildnis gefangen. Welche Entwicklungen haben Zoos durchlaufen und welche Dilemmata haben sich ergeben? Tiere als Objekte? ist eine Online-Publikation von Wissenschaftler:innen des Museums für Naturkunde Berlin, des Berliner Zoos und der Humboldt-Universität zu Berlin, herausgegeben von Ina Heumann und Tahani Nadim. Die Publikation ist Teil des vom BMBF-geförderten Forschungsprojekts "Tiere als Objekte. Zoologische Gärten und Naturkundemuseum in Berlin, 1810 bis 2020". In recent times, zoos have begun advertising themselves as centres for species conservation. Well into the 1970s, however, a majority of their animals had been caught in the wild. What changed zoos and what dilemmas are they facing? Animals as Objects? is an online publication by researchers from the Museum für Naturkunde Berlin, the Zoo Berlin, and the Humboldt-Universität zu Berlin, edited by Ina Heumann and Tahani Nadim. It was funded by the BMBF as part of the research project "Animals as Objects. Zoological Gardens and Natural History Museum in Berlin, 1810 to 2020".

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)0.001
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 score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.002
Science and technology studies0.0060.003
Scholarly communication0.0010.002
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0560.038

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 head0.031
GPT teacher head0.252
Teacher spread0.220 · 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