Maleriets forbandelse jagten på et kunstværk og dets ejere
Bibliographic record
Abstract
I slutningen af 1700-tallet får bogholderen i det mægtige Asiatisk Kompagni malet sit portræt af kunstmaleren Jens Juel. Portrættet er et symbol på rigdom og status, men bogholderen bliver i 1783 del af en kæmpe svindelsag og må gå fra hus og hjem. Maleriet bevæger sig senere gennem historien og trækker et spor af ulykkelige begivenheder efter sig. Sygdom, selvmord og konkurser ser ud til at forfølge ejerne af bogholderens portræt – som hvilede der en forbandelse over det. I Maleriets forbandelse følger to historikere i hælene på maleriet op gennem tiden, og vi møder de forskellige ejere. Det bliver til en sælsom rejse gennem historiens kilder og en forunderlig fortælling om danske rigmænd og kunstsamlere, som på hver deres vis, på tværs af århundreder, er blevet ramt af maleriets forbandelse.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.088 | 0.020 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".