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
At UCLA's Plasma Physics Group, to achieve accessible computational power for our research goals, we developed the tools to build numerically intensive parallel computing clusters on the Macintosh platform. Our technology maximizes productivity because it is designed to allow the user, without expertise in the operating system, to most efficiently develop and run parallel code, enabling the most effective advancement of scientific research. Collaborating with USC and NASA's JPL, our team has demonstrated the performance and scalability potential of Mac clusters by achieving over 217 Gigaflops on 33 XServes and over 233 Gigaflops on 76 Power Mac G4s. but we find that the usability as its performance. The ongoing dessimination of OS X, a Unix-based Mac OS, is providing the best tools of the Mac and Unix in one computing solution. With this development, Mac clustering is becoming the technology that will move parallel computing into the mainstream. See http://exodus.physics.ucla.edu/appleseed/ and http://daugerresearch.com/.
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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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