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
June 01 2014 Introduction Yiftach Fehige, Yiftach Fehige University of Toronto Search for other works by this author on: This Site Google Scholar Michael T. Stuart Michael T. Stuart University of Toronto Search for other works by this author on: This Site Google Scholar Author and Article Information Yiftach Fehige University of Toronto Michael T. Stuart University of Toronto We would like to thank Catherine Z. Elgin, Walter Hopp, and Paul Thagard for contributing original papers, as well as Geordie McComb, Mark Shumelda, and Harald Wiltsche for thoughtful responses to these papers. James R. Brown is to be thanked for his relentless support and generosity in kindness and collegiality. Online ISSN: 1530-9274 Print ISSN: 1063-6145 © 2014 by The Massachusetts Institute of Technology2014 Perspectives on Science (2014) 22 (2): 167–178. https://doi.org/10.1162/POSC_e_00126 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn Email Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Yiftach Fehige, Michael T. Stuart; Introduction. Perspectives on Science 2014; 22 (2): 167–178. doi: https://doi.org/10.1162/POSC_e_00126 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsPerspectives on Science Search Advanced Search This content is only available as a PDF. © 2014 by The Massachusetts Institute of Technology2014 Article PDF first page preview Close Modal You do not currently have access to this content.
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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