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
Notes from the Editor 2 018!The CRP Department is now half-a-century old-a signifcant accomplishment by all standards, particularly considering it continually ranks among the best planning programs in the US.Both the undergraduate and graduate programs get better every year by any measure -the quality of students and their work, the faculty accomplishments, or the feedback from industry.FOCUS serves as one of these measures and as faculty, founder and managing editor I am very proud the journal has been up to the challenge; so much so that we are now celebrating its 15th anniversary!Readers seem happy and the journal is continuously expanding its reach.In fact, according to Cal Poly library's Digital Commons platform, FOCUS readers are counted by the thousands in the US and countries as diverse as Australia, Canada, Great Britain, Chile, Brazil, Nigeria, South Africa, Iran, Turkey, Norway, Japan, Russia, China, and South Korea!Unfortunately, not all were good news this year, as we unexpectedly lost Sierra Russell, one of our most beloved and brilliant alumnus; FOCUS celebrates her life with a modest eulogy.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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