A re-examination of pain–cognition interactions: Implications for neuroimaging
Bibliographic record
Abstract
aInstitute of Medical Science, University of Toronto, Toronto, Canada bDepartment of Surgery, University of Toronto, Toronto, Canada cDivision of Brain, Imaging and Behaviour – Systems Neuroscience, Toronto Western Research Institute, Toronto Western Hospital, University Health Network, Toronto, Ont., Canada M5T 2S8 *Corresponding author. Address: Division of Brain, Imaging and Behaviour – Systems Neuroscience, Toronto Western Research Institute, Toronto Western Hospital, University Health Network, Room MP14-306, 399 Bathurst Street, Toronto, Ont., Canada M5T 2S8. Tel.: +1 416 603 5662; fax: +1 416 603 5745. E-mail: [email protected] 1Present address: McGill Centre for Research on Pain, McGill University, Rm M/19 Strathcona Anatomy & Dentistry, 3640 University Street, Montreal, Que., Canada H3A 2B2. Tel.: +1 514 398 1271; fax: +1 514 398 7464. E-mail: [email protected] E-mail: [email protected] Submitted March 14, 2007; accepted March 27, 2007.
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 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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".