Increasing cannabis use and importance as an environmental contaminant mixture and associated risks to exposed biota: A review
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
For years, cannabis has been largely used for its mind-altering properties. However, the discovery of its medicinal and therapeutic attributes has led to increased medicinal use. With recent legalization of cannabis in Canada, there is an evolving proliferation of the commercial availability of cannabis-containing products, and changes to patterns of use amongst adults are anticipated. Research into the potential harmful effects from increased use due to legalization have begun in humans; however, to our knowledge, investigations into the environmental occurrence and outcomes in fish and wildlife have been largely overlooked. Increasingly potent cannabis strains are also entering both commercial and medicinal sectors thus adding to the potential risk that this product poses to the environment. Indeed, emerging evidence reveals that current wastewater treatment has limited ability to remove bioactive components of cannabis thus allowing their entry into aquatic ecosystems Furthermore, there is very little known regarding the effects, mechanisms and impacts of cannabis exposure in exposed biota, and is currently limited to a few lab-based and field-based studies in a handful of fish species (e.g. zebrafish). This review will discuss the therapeutic uses of cannabis and its constituents, as well as examine its environmental fate and potential to affect aquatic ecosystems in Canada.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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