Bibliographic record
Abstract
Microscopy and Microanalysis 2002 hosted by the Microscopy Society of America (MSA), the Microbeam Analysis Society (MAS), the Microscopical Society of Canada (MSC)/Societe de Microscopie du Canada (SMC), and the International Metallographic Society (IMS) will provide comprehensive Symposia, Tutorials, and Special Sessions covering all aspects of microscopy. Events will begin on Friday, August 2nd with a two-day Pre-meeting Congress chaired by Raynald Gauvin of McGill University entitled “Characterization of non-Conductive or Charging Materials by Microbeam Analysis.” This Pre-meeting Congress will be at McGill University, Montreal, Canada. On Sunday, August 4th, there will be several Short Courses on a variety of topics for those active in teaching, research, and industrial applications involving microscopy and microanalysis. Formal meeting sessions will begin on Monday, August 5th, and will consist of a blend of different presentation formats including Symposia, Tutorials, and Poster sessions that will offer the latest information on cutting-edge discoveries and also provide the opportunity to learn new techniques and procedures. The unique opportunity for “hands-on” learning with state-of-the-art instrumentation will be provided by the integration of the program with the commercial exhibits.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.478 | 0.308 |
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".