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
Biologically induced and controlled mineralization of metals promotes the development of protective structures to shield cells from thermal, chemical, and ultraviolet stresses. Metal biomineralization is widely considered to have been relevant for the survival of life in the environmental conditions of ancient terrestrial oceans. Similar behavior is seen among extremophilic biomineralizers today, which have evolved to inhabit a variety of industrial aqueous environments with elevated metal concentrations. As an example of extreme biomineralization, we introduce the category of "forced biomineralization", which we use to refer to the biologically mediated sequestration of dissolved metals and metalloids into minerals. We discuss forced mineralization as it is known to be carried out by a variety of organisms, including polyextremophiles in a range of psychrophilic, thermophilic, anaerobic, alkaliphilic, acidophilic, and halophilic conditions, as well as in environments with very high or toxic metal ion concentrations. While much additional work lies ahead to characterize the various pathways by which these biominerals form, forced biomineralization has been shown to provide insights for the progression of extreme biomimetics, allowing for promising new forays into creating the next generation of composites using organic-templating approaches under biologically extreme laboratory conditions relevant to a wide range of industrial conditions.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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