Journal of South Carolina Water Resources Volume 1, Issue 1
Bibliographic record
Abstract
For the better part of 2017, South Carolina saw an improvement in drought status for many of the state’s 55 counties, with the SC Drought Response Committee reporting 28 of those in ‘incipient’ (first stage of drought) status and the remaining 17 in ‘normal’ status on November 27. With regard to major rain events, Tropical Storm Irma brought noteworthy levels of rainfall to much of the state in mid-September, as well as coastal flooding. Because of the ongoing significant weather events that continue to threaten water resources and related infrastructure, Clemson’s SC Water Resources Center held its first Summit Series event entitled “Back to the Future of Drought” in April to begin bringing statewide water professionals together for issue specific forums during the ‘off ’ years of the biennial SC Water Resources Conference (SCWRC). The presentations and discussions during the summit fostered new collaborations and shortly after, the SC State Climatology Office took the lead in coordinating a Drought and Water Shortage Tabletop Exercise in September at the SC Emergency Operations Center, drawing 80 participants from across the state. Included in this issue of the journal is a short communication paper about the exercise. Continuing to build on the benefits of statewide networking and collaboration, the SC State Climatology Office has also developed a 2017-18 Climate Connection Workshop series in collaboration with the Carolinas Integrated Sciences and Assessments (CISA) and the Clemson SC Water Resources Center. The first workshop was held in Greenville in December, and workshops are to be scheduled in Columbia and Charleston in early 2018. In addition, SCDNR in partnership with SCDHEC, USGS, Clemson SC Water Resources Center and USACE, held stakeholder meetings during the fall focused on the state’s groundwater assessment. Events such as these, are filling the growing need to initiate collaborative efforts to positively impact water resources management, which in turn continue to grow the network of outreach.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.202 | 0.045 |
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".