Special session 12C: Town-hall meeting “young professionals in test”
Bibliographic record
Abstract
IEEE Test Technology Technical Council (TTTC) takes an initiative to establish a forum involving young professionals working in the broad domain of test, diagnosis, yield improvement and related areas. We have formed a panel involving a diversified group of young professionals (recent PhD graduates from US and Canadian universities) currently employed in the leading US semiconductor and EDA companies. The session will be held in town-hall format, organized by Dr. Alodeep Sanyal from Synopsys and Dr. Yanjing Lin from Intel, and moderated by Dr. Yervant Zorian from Synopsys. The panelists will be involved in discussing the objectives of this newly-formed TTTC forum and the activities it should monitor. Some of the topics of discussion may include: (a) The benefits that TTTC can offer to the young professionals; (b) Establishing a connection between working professionals and graduate students that may provide research/mentoring opportunities for the professionals; (c) An actively maintained job requisition database exclusively available under TTTC for the student members to help them apply for a suitable job. The overall topic of discussion for this panel has been left quite open-ended for participants to propose their own ideas. We expect this panel will identify the future direction and activities for the TTTC Young Professionals Forum.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".