Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>First-Year Seminar (FYS) is an introductory class offered to first-year students to help them acclimate to the college environment, develop effective strategies for studying, and learn techniques that will allow them to swiftly complete small assignments and sizable research projects. In 2014, approximately 80 percent of universities offered FYS, and students who took the course, on average, were less likely to transfer to another school and more likely to receive higher grades. The class allows students to learn more information about the college, select courses that are related to their majors and/or minors, effectively utilize resources while they are studying, cooperate with other students to complete projects, and appreciate the benefits of taking a particular course. FYS also enriches the experiences of first-year students by helping them find organizations of interest, understand university policies, and pursue hobbies while attending the college. At some colleges, students who have already taken a FYS course volunteer to become mentors who provide assistance to first-year students while they are taking the class. Analysis has shown that a high percentage of new enrollees indicated that mentors had a very positive impact on their overall experiences. Moreover, at many colleges and universities, there were increases in the retention rate.</p>
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 it