Ottawa harvested hydrogeological information geodatabase
Bibliographic record
Abstract
Several of the conservation authorities (CA) in eastern Ontario are partnered with the City of Ottawa to provide technical advice about hydrogeological studies that are submitted to the City in support of development applications and about related policy and guidance development. These CA's also facilitate Source Protection initiatives for the local Source Protection Regions and maintain an ongoing partnership with the Ministry of the Environment and Climate Change (MOECC) to collect data from local Provincial Groundwater Monitoring Network (PGMN) wells. In addition, the City also owns information from municipal wells and data from numerous land use monitoring programs. As a result of the above responsibilities, the CAs and City house a tremendous amount of hydrogeological information in separate paper, pdf, tabular, and various old database formats; all of which has never been catalogued. Moreover, this data cannot currently be accessed, summarized, mapped or analysed together. However, there are on-going demands for the presentation and use of this information during the course of regular municipal and conservation authority business. To address the above hydrogeological data management gap, in 2016, the City of Ottawa in partnership with the Rideau Valley Conservation Authority implemented a project to develop a hydrogeological geodatabase and data harvesting plan. This presentation will provide an overview of the project context, outcomes and anticipated next-steps.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.019 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.096 | 0.043 |
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".