Bibliographic record
Abstract
In the lines of a previous paper [1], this contribution will describe the strong influence that David C. Joy had in my research in electron microscopy.As a graduate student, in 1985, I developed my first Monte Carlo program following a paper by David Joy et al. [2] that describes the effect of Fast Secondary Electrons [FSE] on x-ray generation.Their simulations showed that FSE can generate a significant fraction of the x-rays for energy lines below 1 keV.My Monte Carlo simulations showed that FSE can make Cliff-Lorimer K factors composition dependant when one energy line is below 1 keV and the other above [3].I met David Joy the first time at the 1988 EMSA conference of Milwaukee where I asked him several technical questions.He was very nice to answer to a young student.Later, he accepted to be the external evaluator of my Ph.D. thesis that I defended in July 1990.After graduation, I started to work as Assistant Professor at University de Sherbrooke and we started to collaborate.I visited
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".