Bibliographic record
Abstract
This year, Inter/Micro will mark its 70th anniversary (June 11–15, 2018), continuing the vision of its founders, Walter C. McCrone and Charles Tufts, who developed this first of its kind “international microscopy” conference in 1948. Inter/Micro has always been a gathering of microscopists from around the world, and for the past 33 years, it has been held and hosted by McCrone Research Institute in Chicago. Prior to this, the conference alternated between Chicago and various locations in the U.K., including Brighton, Leeds, London, and Cambridge. In the past decade, we have welcomed speakers and attendees from the U.S., the Netherlands, Israel, England, Canada, Australia, Turkey, India, Germany, Taiwan, Norway, and Austria.
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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.019 |
| Insufficient payload (model declined to judge) | 0.020 | 0.015 |
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".