5 Song Set - Episode 17: Old-School Saxophone Jazz
Bibliographic record
Abstract
Episode 17: Old-School Saxophone Jazz 5 Song Set is an eclectic music podcast that plays everything from ragtime to punk. Each episode is five songs long and includes information about the songs and the bands that perform them, as well as other interesting information that varies from show to show. On September 23, 2011, Episode 17 of the podcast was released. In this episode, I have five old school jazz songs for you that feature the saxophone. The songs in this episode are: "Smiles and Chuckles" by Six Brown Brothers "Wringin' and Twistin'" by Frankie Trumbauer and Bix Beiderbecke "I Got Rhythm" by Don Redmon and his Orchestra with Benny Morton "Sittin' In" by Chu Berry "Someone To Watch Over Me" by Ike Quebec More information about the artists and songs can be found in the show notes for the episode . More information is also available at the podcast website, 5songset.net .
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) | 0.932 | 0.214 |
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".