Bibliographic record
Abstract
The hydrologic community lost one of its most charismatic leaders with the death of Paul Witherspoon on 10 February 2012, in Berkeley, Calif. He passed away from complications brought on by his long battle with Parkinson's disease. He was 93. Paul was a dynamic and influential research leader in hydrogeology for more than 50 years. Working from his base at the University of California, Berkeley (UC Berkeley), and later from the Lawrence Berkeley National Laboratory (LBNL), he made significant contributions to the understanding of the flow of fluids in porous media and fractured rock, and he applied his findings to a diverse set of societally important issues, including the development of geothermal energy, use of underground gas storage, and siting and design of nuclear waste disposal facilities. In all these spheres of interest he emphasized the need to marry theoretical studies and field testing. He was especially passionate about the need for large‐scale, in situ, underground experiments to guide and corroborate the predictions of theoretically based numerical models.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".