ResultRST-2026-0101v0.1

Scaffolding response on three easy tasks: SSR = 1.0, 3.1× device energy at A5, 7.9–9.3× at A2–A4

Condition means (quality over available trials / wall s / device J): A0 0.5 / 10.21 / 1715.6; A1 0.5 / 9.87 / 1819.0; A2 0.5 / 79.09 / 15143.0; A3 0.6667 / 99.13 / 15921.5; A4 0.6667 / 69.08 / 13546.2; A5 0.5 / 31.91 / 5321.5. Energy ratio vs A0: A1 1.06, A2 8.827, A3 9.281, A4 7.896, A5 3.102. Total measured GPU energy 0.0891 kWh over 29.9 min of trial time; memory residency rises from 72.1 GiB·s (A0) to 714.6 GiB·s (A3).

Research status: STABLE the current conclusions are relatively stable
Evidence level: E2 Controlled experiment
Result: MIXED
Data basis: REAL MODEL A real language model was executed; the model, its version and its configuration are recorded on the page.
Version: 0.1
Updated: 2026-09-07
Created: 2026-09-03
Domain: Evaluation
Program: PRG-2026-0101 Intelligence Physical Metrology (IPM)
Authors: Neo.K (EveMissLab)
AI collaborators: Aletheia (GPT-5.6 Sol, OpenAI ChatGPT) — 2026-09-07 diagnostic, Splice (Claude Code, Anthropic) — execution and RESULT note

Observed result

metrics

ssr

1.0

sdr

0.0

scm

device_energy_j: 3.1019
wall_time_s: 3.1264

by_condition

A0

quality_mean: 0.5
quality_n: 4
success_rate: 0.5
wall_time_s: 10.21
device_energy_j: 1715.6
energy_ratio_vs_A0: 1.0
gpu_peak_memory_gib: 7.23
gpu_memory_residency_gib_s: 72.1
gpu_utilization_integral_s: 6.57

A1

quality_mean: 0.5
quality_n: 4
success_rate: 0.5
wall_time_s: 9.87
device_energy_j: 1819.0
energy_ratio_vs_A0: 1.06
gpu_peak_memory_gib: 7.32
gpu_memory_residency_gib_s: 70.0
gpu_utilization_integral_s: 6.26

A2

quality_mean: 0.5
quality_n: 4
success_rate: 0.5
wall_time_s: 79.09
device_energy_j: 15143.0
energy_ratio_vs_A0: 8.827
gpu_peak_memory_gib: 7.28
gpu_memory_residency_gib_s: 570.0
gpu_utilization_integral_s: 54.09

A3

quality_mean: 0.6667
quality_n: 3
success_rate: 0.6667
wall_time_s: 99.13
device_energy_j: 15921.5
energy_ratio_vs_A0: 9.281
gpu_peak_memory_gib: 7.34
gpu_memory_residency_gib_s: 714.6
gpu_utilization_integral_s: 70.02

A4

quality_mean: 0.6667
quality_n: 3
success_rate: 0.6667
wall_time_s: 69.08
device_energy_j: 13546.2
energy_ratio_vs_A0: 7.896
gpu_peak_memory_gib: 7.28
gpu_memory_residency_gib_s: 496.9
gpu_utilization_integral_s: 46.93

A5

quality_mean: 0.5
quality_n: 4
success_rate: 0.5
wall_time_s: 31.91
device_energy_j: 5321.5
energy_ratio_vs_A0: 3.102
gpu_peak_memory_gib: 7.24
gpu_memory_residency_gib_s: 228.7
gpu_utilization_integral_s: 22.17

marginal_yield

A0->A1

allocated_device_time_s
device_energy_j: 0.0
wall_time_s

A1->A2

allocated_device_time_s
device_energy_j: 0.0
wall_time_s: 0.0

A2->A3

allocated_device_time_s
device_energy_j: 0.00021406648843853404
wall_time_s: 0.008315919866432606

A3->A4

allocated_device_time_s
device_energy_j
wall_time_s

A4->A5

allocated_device_time_s
device_energy_j
wall_time_s

Interpretation

interpretation: The cost side of the scaffolding response curve is real and steep; the quality side is flat because the tasks were already solved at A0 and because the quality axis was confounded (RST-2026-0102). This is one point on the 'no gap' side of F4 with almost no weight: it neither supports nor refutes the scaffolding-separation hypothesis on non-trivial tasks. The A3/A4 0.667 is not a gain: the aborted CON-003 trials dropped out of the quality denominator and the surviving mean rose.

Limitations

limitations: quality_n is 4 (A0–A2, A5) or 3 (A3, A4) per condition because CODE-001 quality is unavailable and three trials aborted — means over 3–4 values.
Device-measured GPU energy at ~24 % sampling overhead; not marginal energy.

Claims

Source	Relation	Target	Status	ID
`RST-2026-0101` Scaffolding response on three easy tasks: SSR = 1.0, 3.1× device energy at A5, 7.9–9.3× at A2–A4	`qualifies`	`THY-2026-0109` Scaffolding capability record: SSR, SDR, SCM and the ablation ladder	`ACTIVE`	`REL-2026-0486`
`RST-2026-0101` Scaffolding response on three easy tasks: SSR = 1.0, 3.1× device energy at A5, 7.9–9.3× at A2–A4	`qualifies`	`CLM-2026-0104` F4 — Scaffolding separation	`ACTIVE`	`REL-2026-0487`

Relations

Source	Relation	Target	Status	ID
`RST-2026-0101` Scaffolding response on three easy tasks: SSR = 1.0, 3.1× device energy at A5, 7.9–9.3× at A2–A4	`qualifies`	`THY-2026-0109` Scaffolding capability record: SSR, SDR, SCM and the ablation ladder	`ACTIVE`	`REL-2026-0486`
`RST-2026-0101` Scaffolding response on three easy tasks: SSR = 1.0, 3.1× device energy at A5, 7.9–9.3× at A2–A4	`qualifies`	`CLM-2026-0104` F4 — Scaffolding separation	`ACTIVE`	`REL-2026-0487`
`EXP-2026-0103` XA-06 first real-model pilot — Qwythos-9B-v2 on the A0→A5 ladder (36 trials, 2026-09-03)	`produces`	`RST-2026-0101` Scaffolding response on three easy tasks: SSR = 1.0, 3.1× device energy at A5, 7.9–9.3× at A2–A4	`ACTIVE`	`REL-2026-0485`
`RST-2026-0102` Diagnostic: the measured 'quality' was format compliance on 2 of 3 tasks; verifier serialization failed 3/18; the A3/A4 rise is a missingness artifact	`qualifies`	`RST-2026-0101` Scaffolding response on three easy tasks: SSR = 1.0, 3.1× device energy at A5, 7.9–9.3× at A2–A4	`ACTIVE`	`REL-2026-0490`

History and provenance

Canonical URL

https://evemisslab.com/ai/results/RST-2026-0101/

Machine-readable

/ai/results/RST-2026-0101/index.json

Snapshot

AI-SNAPSHOT-v0.1-fe85b9694a45

Provenance

source: EveMissLab research collection: Intelligence Physical Metrology (真本體論13)
extracted_by: Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports
extracted_at: 2026-09-11
generator: tools/extract_all.py
claim_boundary: status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports