Hakai Place Names Service - Coastal British Columbia - Canada
Bibliographic record
Abstract
The place names service is derived from the British Columbia Terrain Resource Information Management Program (TRIM) annotation layer, as well as from place name information from the Hakai Institute. The place names service consists of 4 layers: -TRIM 1:20000 Annotation -TRIM 1:1250000 Annotation -TRIM 1:250000 Annotation -Hakai Place Names The TRIM Annotation metadata is available here http://catalogue.data.gov.bc.ca/dataset/trim-text-annotation More information about the TRIM program is here: http://geobc.gov.bc.ca/base-mapping/atlas/trim/ The Hakai Places Layer has the following attributes: OBJNAM: Name of the feature Landmarks: Code used to classify objects for labelling scale dependencies OBJTYPE: Type of object OBJCLASS: Class of object LABGROUP: Label group category (unused) Processing by: Will McInnes, Keith Holmes (Hakai Institute), and BC Base Annotations data
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.023 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.095 | 0.150 |
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".