Potential negative effects of the Brazilian Space Program on coastal sharks
Bibliographic record
Abstract
The Brazilian government recently announced its first partnerships with the private sector, including American and Canadian companies, to use the Alcântara Space Center (Maranhão, northern Brazil). This center is known for its privileged location, saving up to 30% of fuel in launches. Its operationalization is an offshoot of the Technological Safeguards Agreement, which is important for the Brazilian Space Program due to greater space sector investments and environmentally relevant projects. In 2003, a major fire at the Alcântara Space Center destroyed a rocket and killed 21 workers, halting Brazilian Space Program activities. Recently, our research group reported serious environmental consequences of this accident, i.e., extremely high amounts of Rubidium (Rb) in apex predatory sharks near the Alcântara Space Center. This element is used in fuels and in space propulsion systems and is potentially toxic, displaying bioaccumulating and biomagnifying capabilities. The observed concentrations are the highest ever detected in any living organism (up to 24.65 mg kg-1 dry weight). The launch base is located on the Brazilian Amazon Coast, and population recruitment impacts may compromise biota conservation and biodiversity. Local shark meat consumption is also worrying, as consumers may be exposed to Rb, whose effects in humans are unknown. We, therefore, indicate an urgent need for biomonitoring efforts in the area, as the Alcântara Space Center is about to operate at its maximum capacity.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".