Erratum to “INTIMASY-TBI Guideline: Optimization of INTIMAcy, SexualitY, and Relationships Among Adults With Traumatic Brain Injury”
Bibliographic record
Abstract
Eleni M. Patsakos, MSc; Samantha Backhaus, PhD; Kathryn Farris, OTR/L; Marisa King, PT, DPT; Jhon Alexander Moreno, PhD; Dawn Neumann, PhD; Angelle Sander, PhD; Mark T. Bayley, MD In the article that appeared on pages 395-407 of the September/October 2024 issue of the Journal of Head Trauma Rehabilitation, the affiliations for authors Jhon Alexander Moreno and Angelle Sander were incorrect. The correct affiliations are listed below. Jhon Alexander Moreno, Department of Psychology, Université de Montréal, Montreal, QC, Canada, Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l’Île-de-Montréal (CCSMTL), Montreal, QC, Canada, and Notre-Dame Hospital, CCSMTL, Montreal, QC, Canada. Alexander Moreno, Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas, and Brain Injury Research Center, TIRR Memorial Hermann, Houston, Texas.
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 | 0.004 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.021 | 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".