# std79-doe 3×9 Factorial Analysis — Heartbeat/Physics Telemetry

Generated 2026-09-12 12:45. Source: `combined.csv` (768 rows), built by
`correlate_doe.py` from the three raw logs in
`../results-20260912-with-heartbeat-csv/`. See that file's own docstring for the
correlation methodology (the heartbeat tick's async CSV printer and the DoE trial
loop's own console output share one serial line with no locking, so rows can land
mid-token in the raw logs; the underlying FORTH execution and values are
unaffected, only reconstructing which trial owns which row needed care).

**Design:** 3 architectures (amd64, aarch64, riscv64) × 9 identities (zuse,
rajames, 00-06) × 3 replicates, Fisher-Yates-shuffled run order, same seed
(12345) on every architecture (FABRIC-3.md §XV). Each of the 27 trials per
architecture runs the same 24-word FORTH-79 exerciser; every heartbeat tick during
the whole `EXEC-STD79-DOE` run (bracketed by `HB-ON`/`HB-OFF`) emits one telemetry
row (`doe_log.c`), correlated back to whichever trial was active when it printed.

**Known limitation:** aarch64's raw log lost 1 of 27 run_id markers to interleaving
beyond recovery (trial 12, identity `rajames` rep 1) -- its rows are folded into
trial 11 (identity `rajames` rep 0) in this dataset, so aarch64's `rajames` cell
for rep-sensitive metrics is not perfectly separable for those two replicates
specifically. Every other cell on every architecture is unaffected.

## Key findings (p < 0.05, two-way ANOVA)

- **Architecture main effect:** APIC ticks per heartbeat tick, TIME-TRUST, Timing variance, Hera fleet heat, Hermes fleet heat
- **Identity main effect:** Hot word count, Mean word execution heat, Rolling window width, Actual analysis window size
- **Architecture × identity interaction:** none
- **No significant effect of either factor:** Estimated timer jitter (ns), Max VM call depth, Artemis fleet heat

TIME-TRUST's architecture effect is a numerical artifact worth reading correctly,
not a substantive result: it is essentially constant *within* each architecture
(residual variance ~1e-31, i.e. floating-point noise) and differs *between*
architectures — so the F statistic is enormous simply because the within-group
denominator is near zero, not because TIME-TRUST is meaningfully more variable
across architectures than the other metrics here. It is architecture-determined
and identity-independent, which is itself the interesting part.

## Hot word count (`hot_word_count`)

![Hot word count](svg/hot_word_count.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 67.91 | 1.411 | 2.08 |
| amd64 | rajames | 25 | 64.28 | 7.414 | 11.53 |
| amd64 | 00 | 26 | 64.46 | 7.235 | 11.22 |
| amd64 | 01 | 26 | 62.62 | 6.929 | 11.07 |
| amd64 | 02 | 28 | 62.5 | 6.251 | 10.00 |
| amd64 | 03 | 30 | 62.5 | 5.71 | 9.14 |
| amd64 | 04 | 33 | 66.55 | 5.386 | 8.09 |
| amd64 | 05 | 33 | 64.45 | 3.874 | 6.01 |
| amd64 | 06 | 31 | 65.1 | 3.953 | 6.07 |
| aarch64 | zuse | 23 | 69.35 | 1.191 | 1.72 |
| aarch64 | rajames | 16 | 65.19 | 8.336 | 12.79 |
| aarch64 | 00 | 26 | 62.92 | 7.451 | 11.84 |
| aarch64 | 01 | 27 | 59.81 | 8.005 | 13.38 |
| aarch64 | 02 | 37 | 61.27 | 8.425 | 13.75 |
| aarch64 | 03 | 29 | 60.79 | 7.208 | 11.86 |
| aarch64 | 04 | 33 | 67.48 | 5.745 | 8.51 |
| aarch64 | 05 | 33 | 62.73 | 4.692 | 7.48 |
| aarch64 | 06 | 32 | 63.19 | 4.351 | 6.89 |
| riscv64 | zuse | 23 | 69.48 | 1.039 | 1.50 |
| riscv64 | rajames | 26 | 65.27 | 11.27 | 17.27 |
| riscv64 | 00 | 27 | 62.33 | 8.953 | 14.36 |
| riscv64 | 01 | 28 | 61.68 | 7.252 | 11.76 |
| riscv64 | 02 | 27 | 62.3 | 8.109 | 13.02 |
| riscv64 | 03 | 28 | 63 | 7.123 | 11.31 |
| riscv64 | 04 | 32 | 67.53 | 6.069 | 8.99 |
| riscv64 | 05 | 32 | 65.56 | 5.691 | 8.68 |
| riscv64 | 06 | 34 | 63.85 | 3.839 | 6.01 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 193 | 96.5 | 2.333 | 0.09771 |
| id_label | 8 | 3985 | 498.2 | 12.04 | 2.984e-16 |
| arch:id_label | 16 | 379.9 | 23.74 | 0.574 | 0.9044 |
| Residuals | 741 | 3.065e+04 | 41.36 | — | — |

## Mean word execution heat (`avg_word_heat`)

![Mean word execution heat](svg/avg_word_heat.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 0.003006 | 0.001235 | 41.07 |
| amd64 | rajames | 25 | 0.008839 | 0.008672 | 98.11 |
| amd64 | 00 | 26 | 0.008918 | 0.006694 | 75.06 |
| amd64 | 01 | 26 | 0.01001 | 0.007327 | 73.18 |
| amd64 | 02 | 28 | 0.01069 | 0.004371 | 40.89 |
| amd64 | 03 | 30 | 0.01032 | 0.005016 | 48.61 |
| amd64 | 04 | 33 | 0.004205 | 0.002958 | 70.35 |
| amd64 | 05 | 33 | 0.008833 | 0.001235 | 13.98 |
| amd64 | 06 | 31 | 0.008481 | 0.003743 | 44.13 |
| aarch64 | zuse | 23 | 0.002911 | 0.001418 | 48.72 |
| aarch64 | rajames | 16 | 0.007391 | 0.005726 | 77.48 |
| aarch64 | 00 | 26 | 0.009563 | 0.006967 | 72.85 |
| aarch64 | 01 | 27 | 0.01071 | 0.007785 | 72.67 |
| aarch64 | 02 | 37 | 0.01146 | 0.007358 | 64.20 |
| aarch64 | 03 | 29 | 0.01046 | 0.005237 | 50.05 |
| aarch64 | 04 | 33 | 0.004262 | 0.00298 | 69.93 |
| aarch64 | 05 | 33 | 0.009139 | 0.001443 | 15.79 |
| aarch64 | 06 | 32 | 0.008941 | 0.003745 | 41.89 |
| riscv64 | zuse | 23 | 0.00289 | 0.00163 | 56.41 |
| riscv64 | rajames | 26 | 0.0106 | 0.0133 | 125.42 |
| riscv64 | 00 | 27 | 0.01041 | 0.009052 | 86.95 |
| riscv64 | 01 | 28 | 0.01068 | 0.007445 | 69.74 |
| riscv64 | 02 | 27 | 0.01104 | 0.005331 | 48.29 |
| riscv64 | 03 | 28 | 0.01007 | 0.005873 | 58.30 |
| riscv64 | 04 | 32 | 0.004007 | 0.002863 | 71.45 |
| riscv64 | 05 | 32 | 0.009038 | 0.001403 | 15.52 |
| riscv64 | 06 | 34 | 0.009104 | 0.003387 | 37.20 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 3.325e-05 | 1.662e-05 | 0.5221 | 0.5935 |
| id_label | 8 | 0.005366 | 0.0006707 | 21.07 | 6.051e-29 |
| arch:id_label | 16 | 0.0001362 | 8.514e-06 | 0.2674 | 0.9983 |
| Residuals | 741 | 0.02359 | 3.184e-05 | — | — |

## Rolling window width (`window_width`)

![Rolling window width](svg/window_width.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 256 | 0 | 0.00 |
| amd64 | rajames | 25 | 256 | 0 | 0.00 |
| amd64 | 00 | 26 | 256 | 0 | 0.00 |
| amd64 | 01 | 26 | 256 | 0 | 0.00 |
| amd64 | 02 | 28 | 256 | 0 | 0.00 |
| amd64 | 03 | 30 | 256 | 0 | 0.00 |
| amd64 | 04 | 33 | 318.1 | 192.3 | 60.47 |
| amd64 | 05 | 33 | 256 | 0 | 0.00 |
| amd64 | 06 | 31 | 256 | 0 | 0.00 |
| aarch64 | zuse | 23 | 256 | 0 | 0.00 |
| aarch64 | rajames | 16 | 256 | 0 | 0.00 |
| aarch64 | 00 | 26 | 256 | 0 | 0.00 |
| aarch64 | 01 | 27 | 256 | 0 | 0.00 |
| aarch64 | 02 | 37 | 256 | 0 | 0.00 |
| aarch64 | 03 | 29 | 256 | 0 | 0.00 |
| aarch64 | 04 | 33 | 318.1 | 192.3 | 60.47 |
| aarch64 | 05 | 33 | 256 | 0 | 0.00 |
| aarch64 | 06 | 32 | 256 | 0 | 0.00 |
| riscv64 | zuse | 23 | 256 | 0 | 0.00 |
| riscv64 | rajames | 26 | 256 | 0 | 0.00 |
| riscv64 | 00 | 27 | 256 | 0 | 0.00 |
| riscv64 | 01 | 28 | 256 | 0 | 0.00 |
| riscv64 | 02 | 27 | 256 | 0 | 0.00 |
| riscv64 | 03 | 28 | 256 | 0 | 0.00 |
| riscv64 | 04 | 32 | 296 | 147 | 49.66 |
| riscv64 | 05 | 32 | 256 | 0 | 0.00 |
| riscv64 | 06 | 34 | 256 | 0 | 0.00 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 1575 | 787.7 | 0.1922 | 0.8252 |
| id_label | 8 | 2.57e+05 | 3.213e+04 | 7.839 | 3.816e-10 |
| arch:id_label | 16 | 9163 | 572.7 | 0.1397 |     1 |
| Residuals | 741 | 3.037e+06 | 4098 | — | — |

## Actual analysis window size (`actual_window_size`)

![Actual analysis window size](svg/actual_window_size.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 256 | 0 | 0.00 |
| amd64 | rajames | 25 | 256 | 0 | 0.00 |
| amd64 | 00 | 26 | 256 | 0 | 0.00 |
| amd64 | 01 | 26 | 256 | 0 | 0.00 |
| amd64 | 02 | 28 | 256 | 0 | 0.00 |
| amd64 | 03 | 30 | 256 | 0 | 0.00 |
| amd64 | 04 | 33 | 318.1 | 192.3 | 60.47 |
| amd64 | 05 | 33 | 256 | 0 | 0.00 |
| amd64 | 06 | 31 | 256 | 0 | 0.00 |
| aarch64 | zuse | 23 | 256 | 0 | 0.00 |
| aarch64 | rajames | 16 | 256 | 0 | 0.00 |
| aarch64 | 00 | 26 | 256 | 0 | 0.00 |
| aarch64 | 01 | 27 | 256 | 0 | 0.00 |
| aarch64 | 02 | 37 | 256 | 0 | 0.00 |
| aarch64 | 03 | 29 | 256 | 0 | 0.00 |
| aarch64 | 04 | 33 | 318.1 | 192.3 | 60.47 |
| aarch64 | 05 | 33 | 256 | 0 | 0.00 |
| aarch64 | 06 | 32 | 256 | 0 | 0.00 |
| riscv64 | zuse | 23 | 256 | 0 | 0.00 |
| riscv64 | rajames | 26 | 256 | 0 | 0.00 |
| riscv64 | 00 | 27 | 256 | 0 | 0.00 |
| riscv64 | 01 | 28 | 256 | 0 | 0.00 |
| riscv64 | 02 | 27 | 256 | 0 | 0.00 |
| riscv64 | 03 | 28 | 256 | 0 | 0.00 |
| riscv64 | 04 | 32 | 296 | 147 | 49.66 |
| riscv64 | 05 | 32 | 256 | 0 | 0.00 |
| riscv64 | 06 | 34 | 256 | 0 | 0.00 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 1575 | 787.7 | 0.1922 | 0.8252 |
| id_label | 8 | 2.57e+05 | 3.213e+04 | 7.839 | 3.816e-10 |
| arch:id_label | 16 | 9163 | 572.7 | 0.1397 |     1 |
| Residuals | 741 | 3.037e+06 | 4098 | — | — |

## Estimated timer jitter (ns) (`jitter_ns`)

![Estimated timer jitter (ns)](svg/jitter_ns.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 0 | 0 | — |
| amd64 | rajames | 25 | 7.379e+17 | 3.689e+18 | 500.00 |
| amd64 | 00 | 26 | 7.095e+17 | 3.618e+18 | 509.90 |
| amd64 | 01 | 26 | 9.462e+04 | 4.824e+05 | 509.90 |
| amd64 | 02 | 28 | 6.588e+17 | 3.486e+18 | 529.15 |
| amd64 | 03 | 30 | 1.23e+18 | 4.68e+18 | 380.56 |
| amd64 | 04 | 33 | 5.59e+17 | 3.211e+18 | 574.46 |
| amd64 | 05 | 33 | 5.59e+17 | 3.211e+18 | 574.46 |
| amd64 | 06 | 31 | 5.951e+17 | 3.313e+18 | 556.78 |
| aarch64 | zuse | 23 | 0 | 0 | — |
| aarch64 | rajames | 16 | 0 | 0 | — |
| aarch64 | 00 | 26 | 7.095e+17 | 3.618e+18 | 509.90 |
| aarch64 | 01 | 27 | 6.832e+17 | 3.55e+18 | 519.62 |
| aarch64 | 02 | 37 | 9.971e+17 | 4.229e+18 | 424.10 |
| aarch64 | 03 | 29 | 6.361e+17 | 3.425e+18 | 538.52 |
| aarch64 | 04 | 33 | 5.59e+17 | 3.211e+18 | 574.46 |
| aarch64 | 05 | 33 | 1.118e+18 | 4.47e+18 | 399.80 |
| aarch64 | 06 | 32 | 5.765e+17 | 3.261e+18 | 565.69 |
| riscv64 | zuse | 23 | 0 | 0 | — |
| riscv64 | rajames | 26 | 1.419e+18 | 5.013e+18 | 353.27 |
| riscv64 | 00 | 27 | 6.832e+17 | 3.55e+18 | 519.62 |
| riscv64 | 01 | 28 | 6.588e+17 | 3.486e+18 | 529.15 |
| riscv64 | 02 | 27 | 6.832e+17 | 3.55e+18 | 519.62 |
| riscv64 | 03 | 28 | 6.588e+17 | 3.486e+18 | 529.15 |
| riscv64 | 04 | 32 | 5.765e+17 | 3.261e+18 | 565.69 |
| riscv64 | 05 | 32 | 5.765e+17 | 3.261e+18 | 565.69 |
| riscv64 | 06 | 34 | 1.085e+18 | 4.406e+18 | 406.02 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 2.475e+36 | 1.237e+36 | 0.1045 | 0.9008 |
| id_label | 8 | 4.303e+37 | 5.379e+36 | 0.4543 | 0.888 |
| arch:id_label | 16 | 4.688e+37 | 2.93e+36 | 0.2475 | 0.9989 |
| Residuals | 741 | 8.772e+39 | 1.184e+37 | — | — |

## APIC ticks per heartbeat tick (`apic_delta`)

![APIC ticks per heartbeat tick](svg/apic_delta.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 20 | 2.9 | 1.119 | 38.59 |
| amd64 | rajames | 22 | 2.045 | 4.18 | 204.37 |
| amd64 | 00 | 23 | 2.304 | 3.363 | 145.96 |
| amd64 | 01 | 23 | 2.739 | 1.214 | 44.33 |
| amd64 | 02 | 25 | 3.12 | 2.505 | 80.30 |
| amd64 | 03 | 27 | 3.481 | 2.737 | 78.61 |
| amd64 | 04 | 30 | 3.1 | 1.605 | 51.77 |
| amd64 | 05 | 30 | 1.767 | 6.157 | 348.51 |
| amd64 | 06 | 28 | 2.357 | 5.87 | 249.04 |
| aarch64 | zuse | 20 | 4.45 | 2.585 | 58.09 |
| aarch64 | rajames | 14 | 4.786 | 2.517 | 52.59 |
| aarch64 | 00 | 23 | 3.348 | 7.158 | 213.81 |
| aarch64 | 01 | 24 | 2.75 | 7.651 | 278.23 |
| aarch64 | 02 | 34 | 2.618 | 9.711 | 370.98 |
| aarch64 | 03 | 26 | 3.538 | 3.301 | 93.30 |
| aarch64 | 04 | 30 | 4.3 | 2.409 | 56.02 |
| aarch64 | 05 | 30 | 3.4 | 5.083 | 149.49 |
| aarch64 | 06 | 29 | 2.414 | 10.24 | 424.30 |
| riscv64 | zuse | 20 | 1.35 | 0.6708 | 49.69 |
| riscv64 | rajames | 23 | 1.435 | 2.952 | 205.71 |
| riscv64 | 00 | 24 | 1.667 | 1.761 | 105.67 |
| riscv64 | 01 | 25 | 1.2 | 2.217 | 184.78 |
| riscv64 | 02 | 24 | 1.167 | 2.599 | 222.75 |
| riscv64 | 03 | 25 | 1.16 | 2.939 | 253.40 |
| riscv64 | 04 | 29 | 1.448 | 1.572 | 108.53 |
| riscv64 | 05 | 29 | 1.207 | 3.783 | 313.47 |
| riscv64 | 06 | 31 | 1.452 | 3.414 | 235.19 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 495.9 | 247.9 | 11.21 | 1.626e-05 |
| id_label | 8 | 71.4 | 8.924 | 0.4036 | 0.9187 |
| arch:id_label | 16 | 135.9 | 8.492 | 0.384 | 0.986 |
| Residuals | 661 | 1.462e+04 | 22.11 | — | — |

## TIME-TRUST (`time_trust`)

![TIME-TRUST](svg/time_trust.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 0.6132 | 0 | 0.00 |
| amd64 | rajames | 25 | 0.6132 | 0 | 0.00 |
| amd64 | 00 | 26 | 0.6132 | 0 | 0.00 |
| amd64 | 01 | 26 | 0.6132 | 0 | 0.00 |
| amd64 | 02 | 28 | 0.6132 | 0 | 0.00 |
| amd64 | 03 | 30 | 0.6132 | 0 | 0.00 |
| amd64 | 04 | 33 | 0.6132 | 0 | 0.00 |
| amd64 | 05 | 33 | 0.6132 | 0 | 0.00 |
| amd64 | 06 | 31 | 0.6132 | 0 | 0.00 |
| aarch64 | zuse | 23 | 1 | 0 | 0.00 |
| aarch64 | rajames | 16 | 1 | 0 | 0.00 |
| aarch64 | 00 | 26 | 1 | 0 | 0.00 |
| aarch64 | 01 | 27 | 1 | 0 | 0.00 |
| aarch64 | 02 | 37 | 1 | 0 | 0.00 |
| aarch64 | 03 | 29 | 1 | 0 | 0.00 |
| aarch64 | 04 | 33 | 1 | 0 | 0.00 |
| aarch64 | 05 | 33 | 1 | 0 | 0.00 |
| aarch64 | 06 | 32 | 1 | 0 | 0.00 |
| riscv64 | zuse | 23 | 1 | 0 | 0.00 |
| riscv64 | rajames | 26 | 1 | 0 | 0.00 |
| riscv64 | 00 | 27 | 1 | 0 | 0.00 |
| riscv64 | 01 | 28 | 1 | 0 | 0.00 |
| riscv64 | 02 | 27 | 1 | 0 | 0.00 |
| riscv64 | 03 | 28 | 1 | 0 | 0.00 |
| riscv64 | 04 | 32 | 1 | 0 | 0.00 |
| riscv64 | 05 | 32 | 1 | 0 | 0.00 |
| riscv64 | 06 | 34 | 1 | 0 | 0.00 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 25.48 | 12.74 | 5.379e+31 |     0 |
| id_label | 8 | 1.306e-30 | 1.632e-31 | 0.6892 | 0.7014 |
| arch:id_label | 16 | 2.579e-30 | 1.612e-31 | 0.6806 | 0.8149 |
| Residuals | 741 | 1.755e-28 | 2.369e-31 | — | — |

## Timing variance (`variance`)

![Timing variance](svg/variance.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 0.6307 | 0 | 0.00 |
| amd64 | rajames | 25 | 0.6307 | 0 | 0.00 |
| amd64 | 00 | 26 | 0.6307 | 0 | 0.00 |
| amd64 | 01 | 26 | 0.6307 | 0 | 0.00 |
| amd64 | 02 | 28 | 0.6307 | 0 | 0.00 |
| amd64 | 03 | 30 | 0.6307 | 0 | 0.00 |
| amd64 | 04 | 33 | 0.6307 | 0 | 0.00 |
| amd64 | 05 | 33 | 0.6307 | 0 | 0.00 |
| amd64 | 06 | 31 | 0.6307 | 0 | 0.00 |
| aarch64 | zuse | 23 | 0 | 0 | — |
| aarch64 | rajames | 16 | 0 | 0 | — |
| aarch64 | 00 | 26 | 0 | 0 | — |
| aarch64 | 01 | 27 | 0 | 0 | — |
| aarch64 | 02 | 37 | 0 | 0 | — |
| aarch64 | 03 | 29 | 0 | 0 | — |
| aarch64 | 04 | 33 | 0 | 0 | — |
| aarch64 | 05 | 33 | 0 | 0 | — |
| aarch64 | 06 | 32 | 0 | 0 | — |
| riscv64 | zuse | 23 | 0 | 0 | — |
| riscv64 | rajames | 26 | 0 | 0 | — |
| riscv64 | 00 | 27 | 0 | 0 | — |
| riscv64 | 01 | 28 | 0 | 0 | — |
| riscv64 | 02 | 27 | 0 | 0 | — |
| riscv64 | 03 | 28 | 0 | 0 | — |
| riscv64 | 04 | 32 | 0 | 0 | — |
| riscv64 | 05 | 32 | 0 | 0 | — |
| riscv64 | 06 | 34 | 0 | 0 | — |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 67.75 | 33.88 | 4.293e+32 |     0 |
| id_label | 8 | 6.232e-31 | 7.79e-32 | 0.9873 | 0.4444 |
| arch:id_label | 16 | 1.249e-30 | 7.806e-32 | 0.9893 | 0.4663 |
| Residuals | 741 | 5.847e-29 | 7.89e-32 | — | — |

## Max VM call depth (`vm_call_depth_max`)

![Max VM call depth](svg/vm_call_depth_max.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 1 | 0 | 0.00 |
| amd64 | rajames | 25 | 0.96 | 0.2 | 20.83 |
| amd64 | 00 | 26 | 0.9615 | 0.1961 | 20.40 |
| amd64 | 01 | 26 | 0.9615 | 0.1961 | 20.40 |
| amd64 | 02 | 28 | 0.9643 | 0.189 | 19.60 |
| amd64 | 03 | 30 | 0.9667 | 0.1826 | 18.89 |
| amd64 | 04 | 33 | 0.9697 | 0.1741 | 17.95 |
| amd64 | 05 | 33 | 0.9697 | 0.1741 | 17.95 |
| amd64 | 06 | 31 | 0.9677 | 0.1796 | 18.56 |
| aarch64 | zuse | 23 | 1 | 0 | 0.00 |
| aarch64 | rajames | 16 | 1 | 0 | 0.00 |
| aarch64 | 00 | 26 | 0.9615 | 0.1961 | 20.40 |
| aarch64 | 01 | 27 | 0.963 | 0.1925 | 19.99 |
| aarch64 | 02 | 37 | 0.9459 | 0.2292 | 24.23 |
| aarch64 | 03 | 29 | 0.9655 | 0.1857 | 19.23 |
| aarch64 | 04 | 33 | 0.9697 | 0.1741 | 17.95 |
| aarch64 | 05 | 33 | 0.9394 | 0.2423 | 25.79 |
| aarch64 | 06 | 32 | 0.9688 | 0.1768 | 18.25 |
| riscv64 | zuse | 23 | 1 | 0 | 0.00 |
| riscv64 | rajames | 26 | 0.9231 | 0.2717 | 29.44 |
| riscv64 | 00 | 27 | 0.9259 | 0.2669 | 28.82 |
| riscv64 | 01 | 28 | 0.9643 | 0.189 | 19.60 |
| riscv64 | 02 | 27 | 0.963 | 0.1925 | 19.99 |
| riscv64 | 03 | 28 | 0.9643 | 0.189 | 19.60 |
| riscv64 | 04 | 32 | 0.9688 | 0.1768 | 18.25 |
| riscv64 | 05 | 32 | 0.9688 | 0.1768 | 18.25 |
| riscv64 | 06 | 34 | 0.9706 | 0.1715 | 17.67 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 0.007273 | 0.003636 | 0.1044 | 0.9009 |
| id_label | 8 | 0.1239 | 0.01549 | 0.4447 | 0.8942 |
| arch:id_label | 16 | 0.1016 | 0.006352 | 0.1823 | 0.9999 |
| Residuals | 741 | 25.82 | 0.03484 | — | — |

## Hera fleet heat (`hera_heat`)

![Hera fleet heat](svg/hera_heat.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 0.6532 | 0 | 0.00 |
| amd64 | rajames | 25 | 0.6532 | 0 | 0.00 |
| amd64 | 00 | 26 | 0.6532 | 0 | 0.00 |
| amd64 | 01 | 26 | 0.6532 | 0 | 0.00 |
| amd64 | 02 | 28 | 0.6532 | 0 | 0.00 |
| amd64 | 03 | 30 | 0.6532 | 0 | 0.00 |
| amd64 | 04 | 33 | 0.6532 | 0 | 0.00 |
| amd64 | 05 | 33 | 0.6532 | 0 | 0.00 |
| amd64 | 06 | 31 | 0.6532 | 0 | 0.00 |
| aarch64 | zuse | 23 | 0.6767 | 0 | 0.00 |
| aarch64 | rajames | 16 | 0.6767 | 0 | 0.00 |
| aarch64 | 00 | 26 | 0.6767 | 0 | 0.00 |
| aarch64 | 01 | 27 | 0.6767 | 0 | 0.00 |
| aarch64 | 02 | 37 | 0.6767 | 0 | 0.00 |
| aarch64 | 03 | 29 | 0.6767 | 0 | 0.00 |
| aarch64 | 04 | 33 | 0.6767 | 0 | 0.00 |
| aarch64 | 05 | 33 | 0.6767 | 0 | 0.00 |
| aarch64 | 06 | 32 | 0.6767 | 0 | 0.00 |
| riscv64 | zuse | 23 | 0.6384 | 0 | 0.00 |
| riscv64 | rajames | 26 | 0.6384 | 0 | 0.00 |
| riscv64 | 00 | 27 | 0.6384 | 0 | 0.00 |
| riscv64 | 01 | 28 | 0.6384 | 0 | 0.00 |
| riscv64 | 02 | 27 | 0.6384 | 0 | 0.00 |
| riscv64 | 03 | 28 | 0.6384 | 0 | 0.00 |
| riscv64 | 04 | 32 | 0.6384 | 0 | 0.00 |
| riscv64 | 05 | 32 | 0.6384 | 0 | 0.00 |
| riscv64 | 06 | 34 | 0.6384 | 0 | 0.00 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 0.1909 | 0.09546 | 3.106e+30 |     0 |
| id_label | 8 | 1.995e-31 | 2.494e-32 | 0.8114 | 0.5927 |
| arch:id_label | 16 | 3.935e-31 | 2.459e-32 | 0.8003 | 0.6863 |
| Residuals | 741 | 2.277e-29 | 3.073e-32 | — | — |

## Hermes fleet heat (`hermes_heat`)

![Hermes fleet heat](svg/hermes_heat.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 0.1692 | 0 | 0.00 |
| amd64 | rajames | 25 | 0.1692 | 0 | 0.00 |
| amd64 | 00 | 26 | 0.1692 | 0 | 0.00 |
| amd64 | 01 | 26 | 0.1692 | 0 | 0.00 |
| amd64 | 02 | 28 | 0.1692 | 0 | 0.00 |
| amd64 | 03 | 30 | 0.1692 | 0 | 0.00 |
| amd64 | 04 | 33 | 0.1692 | 0 | 0.00 |
| amd64 | 05 | 33 | 0.1692 | 0 | 0.00 |
| amd64 | 06 | 31 | 0.1692 | 0 | 0.00 |
| aarch64 | zuse | 23 | 0.1581 | 0 | 0.00 |
| aarch64 | rajames | 16 | 0.1581 | 0 | 0.00 |
| aarch64 | 00 | 26 | 0.1581 | 0 | 0.00 |
| aarch64 | 01 | 27 | 0.1581 | 0 | 0.00 |
| aarch64 | 02 | 37 | 0.1581 | 0 | 0.00 |
| aarch64 | 03 | 29 | 0.1581 | 0 | 0.00 |
| aarch64 | 04 | 33 | 0.1581 | 0 | 0.00 |
| aarch64 | 05 | 33 | 0.1581 | 0 | 0.00 |
| aarch64 | 06 | 32 | 0.1581 | 0 | 0.00 |
| riscv64 | zuse | 23 | 0.1762 | 0 | 0.00 |
| riscv64 | rajames | 26 | 0.1762 | 0 | 0.00 |
| riscv64 | 00 | 27 | 0.1762 | 0 | 0.00 |
| riscv64 | 01 | 28 | 0.1762 | 0 | 0.00 |
| riscv64 | 02 | 27 | 0.1762 | 0 | 0.00 |
| riscv64 | 03 | 28 | 0.1762 | 0 | 0.00 |
| riscv64 | 04 | 32 | 0.1762 | 0 | 0.00 |
| riscv64 | 05 | 32 | 0.1762 | 0 | 0.00 |
| riscv64 | 06 | 34 | 0.1762 | 0 | 0.00 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 0.04251 | 0.02125 | 1.491e+31 |     0 |
| id_label | 8 | 9.968e-33 | 1.246e-33 | 0.8744 | 0.5376 |
| arch:id_label | 16 | 1.967e-32 | 1.229e-33 | 0.8627 | 0.6132 |
| Residuals | 741 | 1.056e-30 | 1.425e-33 | — | — |

## Artemis fleet heat (`artemis_heat`)

![Artemis fleet heat](svg/artemis_heat.svg)

| Architecture | Identity | n | mean | sd | CV% |
|---|---|---:|---:|---:|---:|
| amd64 | zuse | 23 | 1.545e+17 | 5.118e+17 | 331.32 |
| amd64 | rajames | 25 | 1.421e+17 | 4.919e+17 | 346.11 |
| amd64 | 00 | 26 | 2.05e+17 | 5.788e+17 | 282.37 |
| amd64 | 01 | 26 | 4.1e+08 | 7.633e+08 | 186.19 |
| amd64 | 02 | 28 | 1.269e+17 | 4.659e+17 | 367.17 |
| amd64 | 03 | 30 | 5.922e+16 | 3.244e+17 | 547.72 |
| amd64 | 04 | 33 | 1.077e+17 | 4.305e+17 | 399.80 |
| amd64 | 05 | 33 | 1.615e+17 | 5.186e+17 | 321.13 |
| amd64 | 06 | 31 | 1.719e+17 | 5.339e+17 | 310.56 |
| aarch64 | zuse | 23 | 7.184e+16 | 3.445e+17 | 479.58 |
| aarch64 | rajames | 16 | 2.065e+17 | 5.643e+17 | 273.25 |
| aarch64 | 00 | 26 | 1.906e+17 | 5.383e+17 | 282.37 |
| aarch64 | 01 | 27 | 3.671e+08 | 6.999e+08 | 190.65 |
| aarch64 | 02 | 37 | 8.931e+16 | 3.788e+17 | 424.10 |
| aarch64 | 03 | 29 | 5.697e+16 | 3.068e+17 | 538.52 |
| aarch64 | 04 | 33 | 1.001e+17 | 4.003e+17 | 399.80 |
| aarch64 | 05 | 33 | 1.502e+17 | 4.823e+17 | 321.13 |
| aarch64 | 06 | 32 | 1.549e+17 | 4.893e+17 | 315.89 |
| riscv64 | zuse | 23 | 8.062e+16 | 3.866e+17 | 479.58 |
| riscv64 | rajames | 26 | 2.853e+08 | 6.822e+08 | 239.16 |
| riscv64 | 00 | 27 | 1.374e+17 | 4.949e+17 | 360.29 |
| riscv64 | 01 | 28 | 3.973e+08 | 7.748e+08 | 195.00 |
| riscv64 | 02 | 27 | 6.868e+16 | 3.568e+17 | 519.62 |
| riscv64 | 03 | 28 | 6.622e+16 | 3.504e+17 | 529.15 |
| riscv64 | 04 | 32 | 5.794e+16 | 3.278e+17 | 565.69 |
| riscv64 | 05 | 32 | 1.159e+17 | 4.56e+17 | 393.50 |
| riscv64 | 06 | 34 | 1.636e+17 | 5.338e+17 | 326.29 |

Two-way ANOVA (`metric ~ arch * id_label`):

| Term | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---:|---:|---:|---:|---:|
| arch | 2 | 2.807e+35 | 1.404e+35 | 0.801 | 0.4492 |
| id_label | 8 | 1.988e+36 | 2.486e+35 | 1.419 | 0.1849 |
| arch:id_label | 16 | 4.978e+35 | 3.111e+34 | 0.1776 | 0.9999 |
| Residuals | 741 | 1.298e+38 | 1.752e+35 | — | — |