Relevance Realization and the Emerging Framework in Cognitive Science
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
Journal Article Relevance Realization and the Emerging Framework in Cognitive Science Get access John Vervaeke, John Vervaeke Cognitive Science Program, and Psychology Department University of Toronto, University College Toronto, ON, Canada, M5S 3H7.E-mail: john.vervaeke@utoronto.ca Search for other works by this author on: Oxford Academic Google Scholar Timothy P. Lillicrap, Timothy P. Lillicrap Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada K7L 3N6.E-mail: tim@biomed.queensu.ca Search for other works by this author on: Oxford Academic Google Scholar Blake A. Richards Blake A. Richards Department of Pharmacology, University of Oxford, Mansfield Road Oxford, OX1 3QT UK.E-mail: blake.richards@pharm.ox.ac.uk Search for other works by this author on: Oxford Academic Google Scholar Journal of Logic and Computation, Volume 22, Issue 1, February 2012, Pages 79–99, https://doi.org/10.1093/logcom/exp067 Published: 27 October 2009 Article history Received: 20 June 2008 Published: 27 October 2009
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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