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.
Bibliographic record
Abstract
Abstract Thallium is highly toxic but has been an obscure element compared to its three popular neighbours, lead, mercury and cadmium. It is partly due to the scarcity of its analytical data, caused by its high analytical detection limit relative to the other three elements and by its generally low level in the environment. We have developed a highly sensitive instrument, a Laser-Excited Atomic Fluorescence Spectrometer, to study thallium contamination in some important Canadian ecosystems from the Arctic (containing very low thallium concentration) to coal-related industries across Canada and even to the study of thallium toxicity in an invertebrate, Hyalella azteca. Overall, our data indicate that the coal power plants and mines contain higher thallium concentrations than the other ecosystems studied, and the eastern region has the highest Tl concentrations compared to other regions. The range of thallium concentration in ng/L for the Arctic snow and ice was between not detected and 8.4, for the Great Lakes waters 0.9 to 48, for pore waters 0.1 to 213, for western coal power plants and mines 0.1 to 1326, for central coal power plants 1.2 to 175, for eastern coal power plants and mines 0.2 to 23605, and for miscellaneous sites across Canada not detected to 4390 ng/L. Some of these high concentrations and those high ones reported in industrial wastewaters exceeded the chronic toxicity endpoints for Hyalella azteca mortality, growth and reproduction, thus can cause serious distress to the environment. All data were integrated into a map of thallium distribution, the first one in Canada. Natural background level of thallium for the Arctic was estimated to be 0.02 to 0.03 pg/g.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it