OGC CHISP-1 Summary Engineering Report
Bibliographic record
Abstract
The CHISP-1 initiative was conducted as a Pilot initiative, which is a collaborative effort that applies technology elements from the OGC Technical Baseline and other (non-OGC) technologies to address Sponsor requirements and scenarios.OGC Pilot initiatives are part of OGC's Interoperability Program, a global, hands-on and collaborative prototyping program designed to rapidly develop, test and deliver proven candidate standards into OGC's Standards Program, where they are formalized for public release.In OGC's Interoperability Initiatives, international teams of technology providers work together to solve specific geo-processing interoperability problems posed by the Initiative's sponsoring organizations.OGC Interoperability Initiatives include test beds, pilot projects, interoperability experiments and interoperability support services -all designed to encourage rapid development, testing, validation and adoption of OGC standards.This report summarizes the results of OGC's Climatology-Hydrology Information Sharing Pilot, Phase 1 (CHISP-1).The objective of this initiative was to develop an interdisciplinary, inter-agency and international virtual observatory system for water resources information from observations in the U.S. and Canada, building on current networks and capabilities.The CHISP-1 Initiative was designed to support these Use Case functions: Hydrologic modeling for historical and current stream flow and groundwater conditions Modeling and assessment of nutrient load into the Great Lakes Suggested additions, changes, and comments on this report are welcome and encouraged.Such suggestions may be submitted by email message to the editor or by making suggested changes in an edited copy of this document (keep Revision Tracking enabled).
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.070 | 0.052 |
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".