My Version of It Live at Primrose on 2024-04-03
Bibliographic record
Abstract
My Version of It Bear, DE Primrose 2024-04-23 (rehearsal) Lineage: IPAD > Reaper > Adobe Audition 01 Lesson #141 (cut) 02 Lesson #120 03 HBO Feature Presentation (cover) 04 Move Closer to Your World (cover) 05 Lesson #29 06 Lesson #59 (clean version) 07 Lesson #228 (first time ever played) 08 Lesson #228 (vocal test) 09 Lesson #229 (first time ever played) 10 Lesson #229 (sped up version) 11 Montreal Metro (high version) 12 Montreal Metro (low version) 13 Lesson #230 [Partial] 14 Secret War (Caligula cover) [Verse Only] 15 Lesson #02 16 Lesson #73 17 Montreal Metro (heavy version) Track 1 appear on Are You Sure Tracks 2, 15, 16 appear on Year of the Comet Tracks 3, 4 appear on At the Mercy of Camouflage Track 5 appears on Gathering Track 6 appears on Saviour Corn Track 14 appears on Delaware Hardcore
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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.643 | 0.074 |
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".