The Effect of an Intense Mentoring Program on Junior Investigators’ Preparation for a Patient-Oriented Clinical Research Career
Bibliographic record
Abstract
PROBLEM: There is a recognized need to translate scientific discoveries to patient-oriented clinical research (POCR). Several obstacles interfere with the successful recruitment and retention of physicians for POCR careers. APPROACH: The American Society of Hematology developed a yearlong educational and mentoring experience, the Clinical Research Training Institute (CRTI), for early-career physician-scientists from multiple institutions throughout the United States and Canada pursuing POCR careers. Several academic outcome measures of the 140 participants in the first seven years (2003-2010) of CRTI were evaluated by reviewing former trainee participants' curriculum vitae and survey responses. OUTCOMES: Ethnic, racial, and gender diversity of CRTI trainees was reflective of the proportions represented across U.S. hematology/oncology fellowship programs. Eighty-six percent (109/126) of trainees reported success establishing a POCR study; nearly half (62/126) had primarily research-focused jobs. Former CRTI trainees received at least 262 external grant awards and published 1,035 peer-reviewed manuscripts, 173 chapters, and 115 review articles. NEXT STEPS: Because mentorship is key to developing a successful career, the CRTI program is being modified to enhance longitudinal mentorship by CRTI faculty mentors and mentors at trainees' home institutions, as well as to encourage the establishment of collaborations and the potential for research project success. Efforts to make the CRTI experience available to more phy sicians, include more CRTI graduates as faculty, and increase participation by hematologists from backgrounds under represented in medicine are under way.
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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 | 0.025 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".