Gai Barone — Patterns 633

In short

Patterns 633 by Gai Barone scores 77/100 in the SOONOS analysis (solid). The strongest dimension is IDENTITY (86/100) and the weakest is SURPRISE (74/100).

This DJ understands that in techno, the space between the notes is as important as the notes themselves.

Key takeaways

Timestamped insights

Each moment below is tagged with how it was produced: “measured” comes from the DSP pass on the audio, “listening” comes from the multi-agent listening pass.

• 4:12Measured (DSP)95/100Listen at 4:12

  A masterclass in patience. The transition is almost imperceptible as the low-end of the new track replaces the old one over 64 bars.

• 9:45Measured (DSP)88/100Listen at 9:45

  Clean handover of the high-hat patterns. The groove remains perfectly stable.

• 12:15Measured (DSP)92/100Listen at 12:15

  Perfectly executed transition that maintains the hypnotic momentum.

• 17:22Measured (DSP)88/100Listen at 17:22

  Smooth introduction of new percussive elements without cluttering the mix.

• 23:12Measured (DSP)90/100Listen at 23:12

  Seamless transition that maintains the hypnotic flow perfectly.

• 29:45Measured (DSP)85/100Listen at 29:45

  Smooth integration of new rhythmic elements, building energy effectively.

About this progressive set

Patterns 633 is a progressive DJ set by Gai Barone, running 1h 27m. It was measured by the SOONOS multi-agent engine and scores 77/100 overall — solid.

The engine files this performance as “Promising”.

This DJ understands that in techno, the space between the notes is as important as the notes themselves.

How the score breaks down

SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 86/100; the weakest is SURPRISE at 74/100.

Analysis coverage for this file is 100% — the share of the set the engine could measure with full confidence.

Energy and structure

The energy curve was sampled at 35 points, moving between 20 and 85 on the SOONOS energy scale — a wide dynamic range across the set.

6 transitions were detected and scored individually.

Beat-grid measurement (DSP) reports 988.2 grid breaks per hour, with a median beat offset of 25 ms.

How this score is built

Measured layer (DSP): the audio file is analysed directly — beat grid, tempo stability, loudness and energy. These values are measurements, not opinions.

Listening layer: a multi-agent pass reads musical intent — programming, storytelling, coherence and crowd effect. This layer interprets, it does not measure.

Fusion and ceilings: the two layers are merged, and the measured layer always wins on execution. When the DSP hears an execution problem, it caps the final score even if the listening layer is positive.

Measured coverage for this file is 100% of the set.

Methodology and limitations

This report is produced automatically from the published recording. It measures what is present in the audio file: a bad source encoding, a partial upload or a heavily processed broadcast version can change the measured values. Nothing here reflects the room, the crowd or the night itself.

Questions about this analysis

What score does Gai Barone's Patterns 633 get?

Patterns 633 scores 77/100 in the SOONOS Mix Database (solid), based on audio measurement plus multi-agent listening.

How long is Patterns 633?

The analysed recording runs 1h 27m.

Which part of the mix scores best?

IDENTITY is the strongest category at 86/100, while SURPRISE is the lowest at 74/100.

How is this score calculated?

SOONOS measures the audio with a DSP pass (beat grid, loudness, tempo, energy) and runs a multi-agent listening pass on top. Measured axes always override the listening layer, so an execution issue heard in the file caps the final score.