Lake Champlain Basin Program: Working together today for tomorrow
Bibliographic record
Abstract
Abstract Lake Champlain is the sixth largest freshwater lake in the USA. Lake Champlain’s watershed is shared by Vermont and New York in the USA, and Quebec in Canada. The lake’s remarkable drainage area to surface area ratio is 19:1. More than 600 000 people live in the Lake Champlain basin and millions visit each year. The lake’s relatively healthy natural resources sustain a thriving economy. The three most challenging environmental issues facing the Lake Champlain basin are reducing phosphorus pollution, preventing toxic contaminants from entering the lake and managing invasive aquatic species that are not native that threaten native flora and fauna. To effectively address these issues, the Lake Champlain Basin Program (LCBP) believes that all decisions about the lake must be based on accurate, ongoing scientific research and that citizen involvement and inter‐jurisdictional cooperation is vital. The programme has worked hard to identify all citizens and organizations that have a stake in Lake Champlain and draw them into a cooperative, sustainable management process. A 1990 Act of Congress (Public Law 101‐596) established a coordinated framework to study and understand the diverse systems of Lake Champlain and its basin in order to develop a comprehensive management plan to protect and restore lake and watershed resources. A 31‐member multi‐stakeholder board was established to develop the plan, a process that took 5 years and included numerous public meetings. Today, a Steering Committee oversees the implementation of the plan and the activities of the LCBP.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.231 | 0.044 |
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".