Abstract: The Ontario Ministry of the Environment and Environment
Bibliographic record
Abstract
established a partnership to develop an aquatic, macro-invertebrate biomonitoring network for lakes, streams, and wetlands. The resultant Ontario Benthos Biomonitoring Network (OBBN) provides a framework for evaluating aquatic ecosystem condition using shallow-water benthos and the reference-condition approach. The OBBN is being developed on the principles of partnership, free data sharing, and standardization. The OBBN protocol outlines field, laboratory, and data-interpretation options which: 1) ensure standardization with proposed federal protocols; and 2), permit partners with varying financial and technical resources to participate. Biological criteria for evaluating aquatic ecosystem condition are generally not available. The OBBN uses a reference-condition approach to bioassessment in which samples from minimally impacted (or reference) sites are used to define the normal range of variation for a variety of indices that summarize biological community composition. Sites where biological health is in question can be evaluated by determining whether test site indices fall within the normal range established from the minimally impacted sites. The OBBN will remove barriers to the application of aquatic biomonitoring techniques across Ontario by specifying standard methods, enabling data sharing between partners, automating analysis using a reference-condition approach, and providing training. EMAN sees the OBBN as a pilot project for a Canada-wide aquatic biomonitoring program.
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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 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.006 |
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".