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
Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsPeter BorweinPETER BORWEIN is a Professor of Mathematics at Simon Fraser University, Vancouver, British Columbia. His Ph.D. is from the University of British Columbia under the supervision of David Boyd. After a postdoctoral year in Oxford and a dozen years at Dalhousie University in Halifax, Nova Scotia, he took up his current position. He has authored five books and over a hundred research articles. His research interests span diophantine and computational number theory, classical analysis, and symbolic computation. He is co-recipient of the Cauvenet Prize and the Hasse Prize, both for exposition in mathematics.Loki JörgensonLOKI JÖRGENSON is an Adjunct Professor of Mathematics at Simon Fraser University, Vancouver, British Columbia. Previously the Research Manager for the Centre for Experimental and Constructive Mathematics, he is a senior scientist at Jaalam Research. He maintains his involvement in mathematics as the digital editor for the Canadian Mathematical Society. His Ph.D. is in computational physics from McGill University, and he has been active in visualization, simulation, and computation for over 15 years. His research has included forays into philosophy, graphics, educational technologies, high performance computing, statistical mechanics, high energy physics, logic, and number theory.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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