SGC - Structural Biology and Human Health: A New Approach to Publishing Structural Biology Results
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
The Structural Genomics Consortium (SGC) is a not-for-profit, public-private partnership established to deliver novel structural biology knowledge on proteins of medical relevance and place this information into the public domain without restriction, spearheading the concept of ''Open-Source Science'' to enable drug discovery. The SGC is a major provider of structural information focussed on proteins related to human health, contributing 20.5% of novel structures released by the PDB in 2008. In this article we describe the PLoS ONE Collection entitled 'Structural Biology and Human Health: Medically Relevant Proteins from the SGC'. This Collection contains a series of articles documenting many of the novel protein structures determined by the SGC and work to further characterise their function. Each article in this Collection can be read in an enhanced version where we have integrated our interactive and intuitive 3D visualisation platform, known as iSee. This publishing platform enables the communication of complex structural biology and related data to a wide audience of non-structural biologists. With the use of iSee as the first example of an interactive and intuitive 3D document publication method as part of PLoS ONE, we are pushing the boundaries of structural biology data delivery and peerreview. Our strong desire is that this step forward will encourage others to consider the need for publication of three dimensional and associated data in a similar manner.
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) | 0.000 | 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 it