FMI applied to the study of the temperature distribution in flip chips
Bibliographic record
Abstract
The use of fluorescent microthermal imaging (FMI) as a tool to study the temperature distribution in flip chip packages was investigated. Backgrinding of the die was required to minimize heat diffusion and maximize the spatial resolution. A test structure was created in order to evaluate FMI spatial resolution from the backside of flip chips as a function of the die thickness and of the power dissipation. A lateral resolution of 50 /spl mu/m is obtained after polishing the die to a thickness of 5 /spl mu/m. At this thickness, the centre of a hot spot can be located with a precision of /spl plusmn/5 /spl mu/m. For a 5 /spl mu/m thick die, the FMI temperature map revealed the heat-sinking effect of the flip chip's solder bumps.
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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 | 0.000 |
| Open science | 0.000 | 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".