Variables du modèle ORI-C
| Variable | Description |
|---|---|
| O(t) | Organisation — Structure interne du système |
| R(t) | Résilience — Capacité d'absorption des perturbations |
| I(t) | Intégration · Cohérence des composants du système |
| V(t) | Viabilité — Agrégation sur [t-Δ, t], fixée ex ante |
| Cap(O,R,I) | Capacité — Forme fixée ex ante |
| Σ(t) | Mismatch — max(0, D(E(t)) - Cap(t)) |
| S(t) | Stock symbolique — Proxies de transmission |
| C(t) | Variable d'ordre — Gain intergénérationnel |
| S₀* | Seuil critique — Estimé à 0.41 (T7) |
Structure du dépôt
v1.3 — Reference lot 22831351459
Nightly #80 — March 8, 2026 — Commit ee3acdf — Branch main — Duration: 20m 55s
The ORI-C framework reaches full closure. Convergent dual proof, validation protocol ACCEPT, contractual and methodological coherence verified.
Canonical tests T1-T8
Synthetic suite — full_statistical (n=60) — Lot 22831351459 — March 8, 2026
Run mode: full_statistical (n=60 runs per condition). All 4 statistical criteria (p_ok, ci_ok, sesoi_ok, power_ok) satisfied on every test.
QCC Brisbane StateProb
Pipeline validated on IBM Brisbane quantum simulator — ISING Algorithm
The ORI-C dynamics — cumulative threshold, regime transition, metastable stability — are observable at the subatomic scale on out-of-equilibrium quantum systems.
First unified framework validated from cosmos to qubits.
The ORI-C signature is detectable on quantum systems with the same robustness as on macroscopic data.
Real data suite
run_real_data_canonical_suite.py — Sources: FRED Monthly, Eurostat — Lot 22831351459
Applied causal tests: Granger, VAR, cointegration, bootstrap CI on observed time series.
Real data verdict: real_data_canonical_support — ACCEPT on reference lot 22831351459.
test_det_rate = 1.0 · stable_det_rate = 0.0 · placebo_det_rate = 0.0 — Perfect separation of all three classes (test, stable, placebo).
Exécuter le pipeline
# Cloner le dépôtgit clone https://github.com/dalozedidier-dot/CumulativeSymbolicThreshold.git cd CumulativeSymbolicThreshold# Installation conda (recommandé)conda env create -f environment.yml conda activate cumulative_symbolic# Ou pippip install -r 04_Code/requirements.txt
# Démo synthétique (transition)python 04_Code/pipeline/run_synthetic_demo.py \ --input 03_Data/synthetic/synthetic_with_transition.csv \ --outdir 05_Results/demo_transition# Démo ORI-C completpython 04_Code/pipeline/run_ori_c_demo.py --outdir 05_Results/ori_c_demo python 04_Code/pipeline/tests_causaux.py --outdir 05_Results/ori_c_demo# Données réelles (pilote CPI)python 04_Code/pipeline/run_real_data_demo.py \ --input 03_Data/real/pilot_cpi/real.csv \ --outdir 05_Results/real/pilot_cpi/run_0001 \ --col-time date --auto-scale --control-mode no_symbolic
Citer ce travail
@software{daloze_2026_oric,
author = {Daloze, Didier},
title = {Cumulative Symbolic Threshold},
year = 2026,
publisher = {OSF},
doi = {10.17605/OSF.IO/G62PZ},
url = {https://osf.io/g62pz/}
}