Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
March 3, 2016. Ellen Wohl, Department of Geosciences, Colorado State University. “Messy Rivers are Healthy Rivers” Perceptions of river health are influenced by expectations regarding the appearance of a natural river, but appearance depends on geomorphic context and river history. I examine how physical complexity – messiness – influences river health, how human activities simplify rivers and compromise river health, and how we can restore complexity and ecosystem services provided by rivers. Wohl is a Fellow of both the Geological Society of America and the American Geophysical Union and has received many awards, including the Gladys W. Cole Memorial Award from the Geological Society of America, the Kirk Bryan Award from the Geological Society of America, the G.K. Gilbert Award from the Association of American Geographers, and the Award for Outstanding Contributions to Interdisciplinary Water Education, Research. March 17, 2016. Donald Worster, University of Kansas. “John Muir and the Religion of Nature: A Bankrupt Legacy?" John Muir and the cause for which he fought, the preservation of wild nature, have been assaulted as tainted by racism, indifferent to the most pressing environmental problems, and bankrupt intellectually and morally. It is time for a new and more fair-minded appraisal of both the man and his cause. Professor Worster has held fellowships from the Guggenheim Foundation, the Australian National University, the National Endowment for the Humanities, the Mellon Foundation, and the American Council of Learned Societies. He has written eight books, which together have won more than dozen book prizes. He is former president of the American Society for Environmental History and a member of the American Academy of Arts and Sciences. April 14, 2016. Laurel Thatcher Ulrich, 300th Anniversary University Professor, History Department. Harvard University. “Adventures in a Natural History Museum.” Henry David Thoreau went to the woods to study nature. Laurel Ulrich and her students went to a Natural History Museum to study Thoreau. There they not only discovered Thoreau’s pond turtle, but a fish that taught them to write, and new vantage point on botany by considering a 116-year-old tortilla. These are only a few of the tangible things Professor Ulrich will explore in her lecture. Ulrich has written six books, including Well-Behaved Women Seldom Make History and A Midwife's Tale, which was later developed into a documentary film for the PBS series American Experience. Ulrich has won the Pulitzer Prize, the Bancroft Prize, and she’s received a MacArthur “Genius Award” Fellowship, among other numerous prizes and distinctions.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it