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Record W4200035023 · doi:10.32920/ifmj.v1i1.1519

Alpenprojekt

2021· article· en· W4200035023 on OpenAlexvenueno aff
Marina Camargo

Bibliographic record

VenueInteractive Film and Media Journal · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology, Conservation, and Geographical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTrilogySkylineHistoryGermanNatural (archaeology)World War IIArt historyArchaeology

Abstract

fetched live from OpenAlex

Alpenprojekt videos register the action of cutting the skyline in the alpine mountains. The footage was taken at different sites in the Alps. The cutouts evoke the European tradition from the 18th century to depict portraits with scissors and paper. A deliberate intent to apprehend the landscape within a unique line in a reduced dimension is the main issue in Alpenprojekt I and II. To react in the face of this specific landscape as an effort to embrace what is not controllable became a fundamental issue in the Alpenprojekt series of works. Alpenprojekt began with artistic research related to the southern German region closely connected with its physical landscape. Its representation was then perceived as a memory heritage of historical facts, either forgotten or intentionally lost. The entire project is called Trilogy of the Mountains, and it is related to memory and history. Trilogy of the Mountains comprises three phases: Alpenprojekt, based on the alpine landscape; the second one approaches Beckton Alps, an artificial mountain in east London; and the third part is related to artificial mountains made with war debris in Germany. Each piece of the Trilogy comprises a series of works. The project was initially developed based on landscapes where the notion of Romanticism is still present. Then the project was set toward the post-industrialization period—and finally related to reshaping the topography in Germany after WWII. In Trilogy of Mountains, the tension between natural and artificial is a central issue, being rather complementary than the opposite.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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 teacher head, not a consensus.

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
Published2021
Admission routes1
Has abstractyes

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