Bibliographic record
Abstract
Chemists around the world participated in the annual #RealTimeChem Week contest Nov. 28 to Dec. 4. The #RealTimeChem hashtag encourages chemists to share photos of their work in progress on Twitter. Blogger Doctor Galactic hosts the annual contest to celebrate and bring awareness to the chemistry community. This year’s theme, #GlobalChem , highlighted the international reach of the #RealTimeChem community. “Chemistry is everywhere and the people who make it happen are too!” Doctor Galactic writes in a blog post announcing the theme . “Did you know that #RealTimeChem has been Tweeted about in over 100 countries around the world?” 95 people from 10 countries participated in the contest, and the seven awards went to people from six countries: Canada, Israel, Mexico, Russia, the UK, and the US. In a departure from previous years, the contest did not have categories; winners were chosen from the overall pool of entries by Doctor
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.256 | 0.165 |
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".