Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ray Brown: His Life and Music is the first full-length biography of Ray Brown, one of the most outstanding practitioners of bass playing in jazz music. Brown’s career spans the most popular and creative eras of jazz, from 1940 to the dawn of the 21st century. During his early professional career, Ray Brown first toured with territory bands, and by 1946, he was hired by Dizzy Gillespie to play in his small group and big band. At this time, Brown became the first call New York bassist to accompany other bop musicians like Charlie Parker and Bud Powell. He also served as the bassist with Norman Granz’s Jazz at the Philharmonic and frequently recorded with an impressive stable of jazz musicians. In 1947 Ray Brown married legendary singer Ella Fitzgerald and soon divided his time by working as the leader of Fitzgerald’s trio while playing with Gillespie, Jazz at the Philharmonic, and as a guest accompanist. After first playing together at Carnegie Hall in 1949, Ray Brown began regularly working with Canadian piano sensation Oscar Peterson until 1965. The Peterson Trio would become one of the most lucrative acts in jazz history. After leaving Peterson, Ray Brown worked as a Los Angeles studio musician and played on numerous commercial recordings but never abandoned swing-based jazz. During these years, he also became involved as a manager, promoter, and teacher. Throughout the mid-1970s until he died in 2002, Ray Brown remained one of the most excellent practitioners of mainstream jazz during a time when some elements of the music moved far away from this style. With so many jazz musicians from his generation succumbing to drugs and tragedy, Ray Brown’s longevity and professionalism are a testament to his talents, intelligence, and professionalism.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.000 |
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 it