The Power of Mentoring: Leveraging Evidence-Based Practice
Bibliographic record
Abstract
Teresa M. Treiger, RN, MA, CCM, FABQAURP, is Commissioner of the Commission for Case Manager Certification, and Principal of Ascent Care Management, Quincy, MA, specializing in private client case management, education, program design, and writing. Her health care career has spanned across the continuum. She designed and implemented case management, transition of care, frequent emergency department utilization, and uncompensated care programs. Her clinical experience includes acute and rehabilitation care. MaryBeth Kurland, CAE, is CEO of the Commission for Case Manager Certification, the first and largest nationally accredited organization that certifies more than 50,000 professional case managers and disability management specialists. The Commission is a nonprofit, volunteer organization that oversees the process of case manager certification with its CCM credential and the process of disability management specialist certification with its CDMS credential. Address correspondence to MaryBeth Kurland, CAE, Commission for Case Manager Certification, 1120 Route 73, Ste 200, Mount Laurel, NJ 08054 ([email protected]). The authors report no conflicts of interest.
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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 | 0.268 | 0.409 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.028 | 0.024 |
| Open science | 0.006 | 0.032 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".