Reply to Carreira-Perpiñán and Goodhill
Bibliographic record
Abstract
September 01 2002 Reply to Carreira-Perpiñán and Goodhill In Special Collection: CogNet Nicholas V. Swindale, Nicholas V. Swindale Department of Ophthalmology, University of British Columbia, Vancouver, B.C., V5Z 3N9, swindale@interchange.ubc.ca Search for other works by this author on: This Site Google Scholar Doron Shoham, Doron Shoham Weizmann Institute of Science, Department of Neurobiology, Rehovot 76100, Israel Search for other works by this author on: This Site Google Scholar Amiram Grinvald, Amiram Grinvald Weizmann Institute of Science, Department of Neurobiology, Rehovot 76100, Israel, Amiram.Grinvald@weizmann.ac.il Search for other works by this author on: This Site Google Scholar Tobias Bonhoeffer, Tobias Bonhoeffer Max-Planck-Institut für Neurobiologie, D-82152 Martinsried, Germany, tobias.bonhoeffer@neuro.mpg.de Search for other works by this author on: This Site Google Scholar Mark Hübener Mark Hübener Max-Planck-Institut für Neurobiologie, D-82152 Martinsried, Germany, mark@neuro.mpg.de Search for other works by this author on: This Site Google Scholar Author and Article Information Nicholas V. Swindale Department of Ophthalmology, University of British Columbia, Vancouver, B.C., V5Z 3N9, swindale@interchange.ubc.ca Doron Shoham Weizmann Institute of Science, Department of Neurobiology, Rehovot 76100, Israel Amiram Grinvald Weizmann Institute of Science, Department of Neurobiology, Rehovot 76100, Israel, Amiram.Grinvald@weizmann.ac.il Tobias Bonhoeffer Max-Planck-Institut für Neurobiologie, D-82152 Martinsried, Germany, tobias.bonhoeffer@neuro.mpg.de Mark Hübener Max-Planck-Institut für Neurobiologie, D-82152 Martinsried, Germany, mark@neuro.mpg.de Received: November 20 2001 Accepted: February 25 2002 Online ISSN: 1530-888X Print ISSN: 0899-7667 © 2002 Massachusetts Institute of Technology2002 Neural Computation (2002) 14 (9): 2053–2056. https://doi.org/10.1162/089976602320264006 Article history Received: November 20 2001 Accepted: February 25 2002 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 Nicholas V. Swindale, Doron Shoham, Amiram Grinvald, Tobias Bonhoeffer, Mark Hübener; Reply to Carreira-Perpiñán and Goodhill. Neural Comput 2002; 14 (9): 2053–2056. doi: https://doi.org/10.1162/089976602320264006 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 JournalsNeural Computation Search Advanced Search This content is only available as a PDF. © 2002 Massachusetts Institute of Technology2002 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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.034 | 0.041 |
| Insufficient payload (model declined to judge) | 0.018 | 0.018 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".