Evidence of effect of riparian attributes on listed freshwater fishes and mussels and their aquatic critical habitat: a systematic map protocol
Bibliographic record
Abstract
Abstract Background Habitat that is necessary for the survival and recovery of a species listed as threatened, endangered or extirpated (i.e., Critical Habitat) is protected in Canada. For freshwater aquatic species, Critical Habitat may include the riparian zone, however, it is unclear how much of this riparian habitat needs to be protected to support the survival and recovery of a listed species. The riparian zone mainly affects aquatic species through its indirect effect on aquatic habitat according to five main processes: erosion, filtration, infiltration, shading, and subsidization. To provide quantitative evidence to support the delineation of riparian Critical Habitat, a systematic map will be used to create a searchable database containing the current state of knowledge regarding the relationships between the riparian zone attributes (e.g., size, vegetation) and fishes and mussels, aquatic features, and riparian processes. Methods We will search for primary research articles in bibliographic databases and relevant organizational websites for primary literature, theses, preprints, and grey literature including reports, along with models using a search string specific to riparian habitat. The results will be screened at title and abstract, and full text levels against predefined inclusion criteria and consistency checking will be performed to ensure the inclusion criteria are consistent across multiple reviewers. Quantitative and qualitative data including study details and methods, the riparian habitat, and the waterbody and upland habitat use will be extracted. The findings of the systematic map will be provided in a manuscript and a searchable database accompanied by a decision tree to support biologists in providing scientifically defensible delineation of riparian Critical Habitat for aquatic species at risk 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.
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 | 0.082 | 0.164 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.048 | 0.023 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.007 |
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".