An Object Model For Geologic Map
Bibliographic record
Abstract
National geologic map databases are presently being constructed in the U.S. and Canada, as well as in several other countries. Here, we describe an object-based model for geologic map information, specifically designed to represent digital geologic maps and related geoscientific information. Although oriented to geoscience, several fundamental issues in representing geospatial information are explored in this design, including the philosophic and cognitive basis of mapping in general, and the overall framework in which map-related information can be represented. Thus we take an ontologic approach to geospatial representation, supplemented by an epistemic view of the scientific process, which culminates in a very general model---a meta-model---for map information. Practical as well as theoretical considerations motivate this approach. Primarily, however, we describe the theoretical foundations of our meta-model, specifically semiotics, category theory, and ontology in geospatial information. Finally, we report briefly on a specific prototype data model derived from the meta-model and implemented in a commercial object-oriented GIS.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".