Bibliographic record
Abstract
ABSTRACT Sponsored by: SMTA San Diego Chapter Handling of moisture sensitive packages is an ongoing learning process in volume manufacturing. Improperly handled and stored MSDs can impact yields and reliability. The presentation will cover a review of the industry standards for MSDs( J-STD-020, J-STD 033 and J-STD 075) and their applications in moisture control. PWBs used for assembly also require controlled storage and handling. Board surface finishes, storage and baking guidelines will be reviewed per the IPC 1601 standard. Handling of MSDs from receipt to use at reflow will be reviewed, including practical guidelines in labelling, tracking, packing, storage and supplier audits. About the Presenter Mumtaz Y. Bora has a B.S. in Chemistry and Material Sciences from University of Mumbai, India and University of Ottawa, Canada. She has a Master of Science in Interactive Telecommunications from University of Redlands, California. She has over 25 years of PWB, SMT assembly and advanced packaging development experience at IBM Endicott and IBM Austin, TX. She has worked in new product development, and qualification of high volume handset assemblies at Qualcomm and Kyocera-Wireless Corporation. She has worked with suppliers and subcontractors in several parts of Asia. She is currently a Sr. Staff Packaging Engineer at pSemi for qualification of wire bonded and flip chip RFIC packages for wireless, broadband, Automotive and Hi-Rel/Space applications. She is a member of IPC standardization committees and contributes to the standards development. She has 16 publications and 3 patents. She is the VP of Communication for SMTA San Diego chapter and Co-chair of the SMTA Moisture Sensitive Devices Council. She is currently a publicity chair for IMAPS San Diego chapter. On Demand Webinar
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".