Titanium, Titanium Alloys, and Titanium Compounds
Bibliographic record
Abstract
Abstract The article contains sections titled: 1. Introduction 2. Physical Properties 3. Mechanical Properties 4. Corrosion Behavior 5. Occurrence 6. Production of Titanium Tetrachloride 7. Production of Titanium Sponge 7.1. Reduction of Titanium Dioxide 7.2. Reduction of Titanium Halides 7.3. Thermal Decomposition of Titanium Halides 7.4. Electrowinning of Titanium 8. Processing and Reuse of Scrap Metal 9. Processing of Titanium Sponge 10. Production and Processing of Semifinished Products 11. Titanium Alloys 11.1. α‐, (α + β)‐, and β‐Alloys 11.2. Highly Alloyed Titanium 12. Uses and Economic Aspects 13. Titanium Master Alloys 13.1. Ferrotitanium 13.1.1. Composition and Uses 13.1.2. Production 13.1.3. Economic Aspects 13.2. Titanium ‐ Aluminum 13.3. Other Master Alloys 14. Titanium Compounds 14.1. Titanium(II) Compounds 14.2. Titanium(III) Compounds 14.3. Titanium(IV) Compounds 14.4. Interstitial Compounds 15. Toxicology and Occupational Health
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.137 | 0.055 |
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".