The Rehabilitation Professional & Journal of Life Care Planning: A Year in Review
Bibliographic record
Abstract
I am thrilled to be writing to you in the augural Year in Review issue. In this issue, we hope to highlight for all of our members some of the outstanding articles that have appeared within the 2021 issues of The Rehabilitation Professional and the Journal of Life Care Planning. As I write this in November 2021, IARP has 1,611 members who hail from multiple professional disciplines and perform various types of rehabilitation-centered work. Yet, we each value what IARP provides to our professional endeavors. It is IARP’s goal to provide offerings that each member finds useful. The needs of a member who provides transition services in the southern United States vary from the member who provides life care planning in Newfoundland and Labrador, yet as an organization IARP’s goal is to meet the needs of both of these members. This is no small feat for IARP to accomplish.
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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 | 0.012 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".