Bibliographic record
Abstract
Growth and Form: What is the Aim of Biomineralization SILICA-HYDRATED POLYSILICONDIOXIDE Collagen, a Huge Matrix in Glass Sponge Flexible Spicules of the Meter-long Hyalonema Sieboldi Molecular Genetic and Biochemical Tools for the Analysis of Diatom Cell Wall Formation Formation of Siliceous Spicules in the Marine Demosponge Suberites Domuncula Development of Advanced Mechanical Defenses of Diatom Shells Evolution of Diatoms Uptake of Silicon in Different Plant Species IRON SULFIDES AND OXIDES Magnetic Microstructure of Magnetotactic Bacteria An Archeal Ferritin: First Step in its Iron Cluster Formation Physiology and Genetics of Magnetite Crystal Formation in Magnetotactic Bacteria Physical and Chemical Principles of Magnetosensation in Biology CALCIUM CARBONATES AND SULFATES The Morphogenesis and Biomineralization of Sea Urchin Laval Spicules Coccolith Formation in Pleurochrysis Carterae: Structural and Molecular Approaches Molecular Approaches to Emiliana Huxleyi Coccolith Formation Organic Matrix and Biomineralization of Scleractinian Corals Statoliths, Calcium Sulfate Hemihydrate Crystals, are Used for Gravity Sensing in Scyphozoan Medusa (Cnidaria) Unusually Acidic Proteins in Biomineralization Fish Otolith Calcification in Relation to Endolymph Chemistry Eggshell Growth and Matrix Proteins CALCIUM PHOSPHATES Genetic Basis for the Evolution of Vertebrate Mineralized Tissue Skeletogenesis in Zebra Fish Embryos (Danio Rerio) Synchroton-Radiation Based Micro Computer Tomography Applied on Zebra Fish Bone and Teeth Mechanical and Structural Properties of Skeletal Bone in Wild-Type and Mutant Zebra Fish (Danio Rerio) Nanoscale Mechanism of Bone Deformation and Fracture Formation and Structure of Calciprotein Particles: The Calcium Phosphate-Ahsg/FetuinA Interphase
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.
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 | 0.000 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".