— part of a multi-departmental series on applying for City services What Are Survey
Bibliographic record
Abstract
Survey monuments are physical markers indicating the location of land boundary corners, geodetic control points, or local control points. They enable a surveyor to relate narrative boundary descriptions or improvements, and boundaries drawn on a set of plans to the actual location on the ground. Why Are Survey Monuments Important? All real properties, such as parcels, lots, rights-of-way, and easements can only be located or staked on the ground by starting from a monument. Legal descriptions of the horizontal and vertical locations of properties and structures all require the location of a monument as their beginning point of reference. The accuracy and relevancy of the City’s Geographic Information System (GIS) maps are also based on survey monuments. The network of survey monuments protects and delineates public and private property, and is critical to the enforcement and enjoyment of real property rights. Survey monuments are important assets belonging to the City and its citizens, and are protected and maintained as such. How to Locate or Identify a Survey Monument? Most Survey Monument locations can be found in the City’s GIS system and on the City’s Quarter Section Maps (also called Engineering Maps). The City’s Survey Field Books can also help determine monument locations. These books may show how a monument was set, and what condition it was in when it was last seen. The books may also where there may be ties to a monument, if the monument has been buried or lost. Survey Monuments used for horizontal location are typically found in the City’s Right of Way (ROW), typically in the center of the ROW, and most often at intersections. However, some monuments have
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.499 | 0.454 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".