Bibliographic record
Abstract
The Flow State EP is inspired by Mihaly Csikszentmihalyi’s ideas that flow states - those moments when you are completely absorbed by something - are a secret to happiness. The tracks aim to engage with what different contexts describe as ecstatic trance, altered states, entrainment, or unconscious processes, looking for connection with oneself through presence in the body and stillness of the mind. Influenced by a syncretic fusion of a number of mystical traditions, as well as the study of the sonic cultures of our ancient ancestors, the intention is to provide you with a place that affords enough space to be, rather than to think. Professor Chill is a longstanding fixture of the chill out scene, with a mixed background as both an electronic music producer and a qualified sound scientist. Unlike the colourific professors Green and Plum, Professor Chill was awarded his very real title as a result of his academic career, having studied with composers such as Gavin Bryars and Katharine Norman, gaining the first ever PhD for writing any kind of popular music. At the same time as his intellectual studies, he has written, released and performed electronica; his last album Dub Archaeology was released in 2018 on Twin Records and you might have seen him performing live at European music festivals such as Glastonbury, Boom, Anthropos, Schiev, Samsara, Utiopia, or CTM. His influences are very broad, but there’s something of Leftfield, Eno, Groove Armada, John Cage, and Deep Forest in there, generating an uplifting mixture of gentle groove and tuneful tranquillity. This new EP of euphoric electronica features two solo tracks and three collaborations with Sheffield linked artists: ‘Beauty’ was co-written and produced with Anne Garner, who also plays flute on the track; ‘Dawning’ was a joint production with Planet Zogg promoter and DJ Johnny M; ‘Lost Boys and Sand Dunes’ was co-produced with Andy Vonal, who is perhaps better known as techno producer Vonal KSZ, and features folk singer Tegwen Roberts.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.231 | 0.073 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".