rd Workshop for Doctoral Students in Object-Oriented Systems
Bibliographic record
Abstract
. This is a summary of the 3rd Workshop for Doctoral Students in Object-Oriented Systems. This document presents the activities and results of the sessions of the workshop. In the Ph.D. network session the usage and evolution of the Ph.D. mailing list was elaborated. The corresponding chapter contains also an introduction to the goals of the list including the access rules. In the main non-technical session planning of research was discussed. The session was supported by an invited talk of Oscar Nierstrasz. The technical session practised the work in groups and the ability of writing. 1 Introduction In conjunction with ECOOP `93 a one day workshop for 15 Ph.D. students was held. Most of the students came from European universities, but there was also a student from Canada. The workshop was the 3rd in a series of workshops held in conjunction with ECOOP conferences. They are intended to advance the personal and professional development of Ph.D.-level students working in the field of ob...
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.083 | 0.045 |
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".