[ AZWDC 003] Flute Of Shaytan. Vol. III
Bibliographic record
Abstract
mp3, CBR 128 kbps 1. Wallmaster (Canada) - Untitled (4:40) noise All Recordings - Jason Campbell 2. Sonitus Haigus (Russia) - Wreid (11:02) harsh noise All recordings - Kiladeer 3. Schwargleis (Russia) - 1825 (4:21) noise ambient All recordings - Dmitry K. 4. Angel Of Mercy (Australia) - Untitled (5:01) hnw All recordings - Luke Pooley 5. Noise Jihad (Russia) - Jerusalem (4:42) harsh noise/hnw All Recordings - a.v. 6. Virtual Mosque (Russia) - #inshallah (1:34) harsh noise/experimental All Recordings - a.v. 7. Catacombs Of Doom (Greece) - The Great Deceiver (3:00) dark ambient Synths, drone, fx - Bill Kibizis synths, Bass - Dimitris Kalyvas Guitars, drums - Donn (Teutoburg Forest) UK 8. Burkha ???? (USA) - Children Playing In An Alleyway In Mosul (4:52) noise/industrial All Recordings - Himeko Katagiri 9. Marid (Russia) - Schaam (5:03) ambient All recordings - Marid 10. Humanslave (USA) - Allahu ak(47)bar (3:58) harsh noise All recordings - Benedict Hall 11. Mujahideen (Russia) - Mullah Dance (2:12) noise ambient All recordings - Nick Masodov 12. Hargeysa (Russia) - New Somalia (2:42) dark ambient/wall ambient All Recordings - a.v. 13. Lazokna (Russia) & Noise Jihad (Russia) - Галерея Памяти. Шахиды в Судный День (7:32) ready-made Original track by Timur Mutsuraev
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 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) | 0.447 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".