Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
By paying insufficient attention to the physical, solid-state properties of drug compounds, the pharmaceutical industry has missed opportunities for new drugs and imposed untold costs on itself, according to a group of industry leaders. Drug companies can better carry out their core duty—creating new medicines—by drawing more rigorously on materials science and engineering and translating this fundamental science into pharmaceutical development, they say. To promote this goal, the group launched the M3 conference, named for “Molecules, Materials, Medicines.” The third M3 meeting took place on May 19–22 in Banff, Alberta. The group includes Örn Almarsson and Magali Hickey of Alkermes, Patrick Connelly and Michael (Mick) Hurrey of Vertex Pharmaceuticals, Drazen Ostovic of KO Pharm R&D, Matt Peterson of Amgen, and Elizabeth B. Vadas of InSciTech. For years, they advocated for earlier and more rigorous application of solid-state materials science in pharmaceutical R&D. They argued, both in their own workplaces and ...
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.
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) | 0.001 | 0.001 |
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 it