Norman Fairbanks - Graceland EP [tube039]
Bibliographic record
Abstract
«Now for some easy chillout breaks, for a change. LA based Norman Fairbanks doesn't do what we like to call 'difficult listening music'. No, he doesn't. Instead, he crafts some of the best lie-down-and-try-not-to-think kind of tunes that I've had the pleasure to listen to this year. Take a look at his website and tell me if those Hollywood streets aren't just the perfect scenario to enjoy the kind of lush downbeat tracks that make up this Graceland EP, while driving to your Corvette at cruise speed. If you've listened to Norman's previous release on Pentagonik - West Hollywood EP -, you'll see that this is a rather different outfit. Instead of electro beats we've got smooth pads. Instead of body dance music we've got mind chill electronica. Opener 'PCH1' stands for 'Pacific Coast Highway 1' and features very nice drumpads and all around great chillness. Sooothing synth melodies and quirky old school hi-hats with a dubbish reverb feel are also included. 'Mystified' goes back to Boards of Canada's earlier future nostalgia material, nineties. Starts off with acoustic guitar plucking, very pastoral, and turns into the most danceable track of the EP. '90026' goes more downbeat ways again with more old school synth lines, and 'Graceland' finishes off with more upbeat beat programming, close enough to minimal techno that one could easily dance to it. This EP perfectly encapsulates the sunset drive-by-feel of hollywood streets and boulevards. Chillout, LA style. Enjoy.» - Pedro Leitão
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.455 | 0.245 |
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; the direct Gemma label and the distilled Codex classifier 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".