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
Abstract Advancements in the synthesis of sulfur‐rich materials are driving progress across diverse fields owing to the rich and tunable functionalities of those materials. These materials are typically valued for their electrochemical behaviors, high refractive indices, heavy metal affinity, and ability to form dynamic covalent bonding. As a result, their applications span various industries including electronics, catalysis, lithium‐sulfur batteries, water reclamation, and optoelectronics. Moreover, elemental sulfur, a byproduct of the petroleum industry, is produced abundantly, necessitating the exploration of novel valorization routes for polymers made from this feedstock. The unique combination of properties of sulfur‐rich polymers also makes them an ideal platform for the development of high‐performance functional coatings, offering durability and tailored functionalities for protective coatings, thus enhancing materials lifespan and performances in a variety of environmental conditions. The presence of dynamic covalent bonds in many sulfur‐rich polymers enables the creation of self‐healing coatings, while sulfur itself or the comonomers can contribute to antimicrobial, antifouling, and corrosion‐resistant properties. Furthermore, sulfur‐rich polymers have the potential to be used in the design of icephobic and superhydrophobic coatings. This underscores the versatility of sulfur‐rich polymers as a platform for the creation of advanced coatings with superior properties.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.031 | 0.003 |
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