Bibliographic record
Abstract
An Arc View GIS (geographic information system) interface has been created for viewing and facilitating development of USEPA SWMr\r1 RUNOFF and EXTRAN models.The interface is a group of A venue scripts that allow users to visualize a SWMM model in conjunction with existing GIS data.(Avenue is a programming language bundled with ArcView.)The rationale for using Avenue/ArcView as a platform for a SWM,_\1 GIS tool has been previously presented by Shamsi (1998).The scripts have been published as freeware, allowing easy access for other SWMM modelers and offering users the oppmiunity to make their own enhancements, similar to the communal efforts that have characterized SWMM advancements over the years.The scripts permit viewing of model input and output summary data \J¥1.thinArc View, allowing modelers to exploit GIS tools for analyzing model configurations and output.They do not substitute for existing commercial software interfaces for SWMM, as they do not permit viewing of conduit profiles, dynamic display of results, or editing of input data.Arc View's strengths do not lie in display of three-dimensional or dynamic data, so it would be cumbersome to develop such tools within Arc View.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.125 | 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".