Bibliographic record
Abstract
The Trace Evidence video trilogy explores the geological, meteorological, and hydrological appearance of nuclear evidence secreted within the molecular arrangement of matter. Its focuses upon three events: the unearthing of ancient nuclear reactors at the uranium mine site in Oklo, Gabon in 1972, the discovery of Chernobyl’s airborne contaminates at the Forsmark power plant in Sweden in April 1986 and the 7,600 kilometre five year journey of Caesium-137 from Fukushima-Daiichi through the waters of the Pacific Ocean to the west coast of Vancouver Island. Within environmental justice work, establishing the incontrovertible relationship between cause and effect has proven a difficult legal challenge. The spatial dispersal of contaminates and temporal latency of their material and biological effects, which may take years, even decades to emerge, has allowed global climate-change actors and states to operate with virtual impunity. But the nuclear isn’t like other complex, non-linear events. Despite its radical and covert nature, the unique signature and behaviour of radioactive isotopes allows its lethal traces to be tracked directly back to their source, re-connecting, in effect, the evidential links that planetary phenomena has seemingly torn asunder.
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 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 | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.335 | 0.088 |
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".