Ecological Screening Assessment of Selected Surfactants under the Government of Canada’s Chemicals Management Plan
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
Under the Chemicals Management Plan (CMP), the Government of Canada is assessing and managing, where appropriate, the human health and ecological risks of substances. Building on the first 2 phases of the CMP (2006-2015), 1550 substances have been identified for the third phases of the CMP. These substances will be assessed over the coming five years. Surfactants known as the alkyl aryl sulfonates/linear alkyl benzene sulfonates (LABS) and derivatives, are among those identified as priorities for action in the third phase of the CMP (starting 2016). The selection of these substances is based on the categorization process completed in 2006. A screening assessment for these substances will be conducted under the Canadian Environmental Protection Act, 1999 (CEPA). the Government of Canada will apply wight of evidence and precaution in decision-making to determine whether the substance may be toxic as defined in Section 64 of the Act. For the ecological risk assessment, all available data for various media will be considered, including chemical analogues for "read-across" purposes and computer models. Where data is limited, conservative assumptions will be applied in the ecological risk assessment for factors such as the potential for theses substances to degrade or metabolize; the potential for these substances to bioaccumulate; and the potential for these substances to cause harm to biota in the environment. A 60-day public comment period will follow the publication of the draft screening assessment for these substances. This poster provides a description of the ecological assessment process for the alkyl aryl sulfonates/LABS and derivatives under the CMP.
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 | 0.000 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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