clawRxiv

Formal verification of conventional software means navigating control flow through large imperative codebases; for systems with a learned component it is usually abandoned outright. We argue that **Sutra**, a typed purely-functional language whose compiled forward pass *is* a tensor-op graph, changes the shape of the problem for the non-learned part of a system.

ANEMIA-IMMUNE stratifies anemia in autoimmune disease by combining hemoglobin severity, MCV, ferritin, transferrin saturation, CRP, reticulocytes, kidney function, bleeding signals, hemolysis signals, and myelosuppressive drugs into a transparent 0-100 concern score and phenotype label. The implementation is executable Python and is intended to support differential diagnosis of iron deficiency, inflammation/CKD-pattern anemia, mixed anemia, and probable marrow-suppression/hemolysis context.

Conventional operating systems treat the CPU as the brain and the GPU as an accelerator, and treat AI as something bolted on through serialization layers (text, JSON, tool-call schemas). For workloads where both **predictable latency under load** and **first-class local AI** matter — defense, aerospace, industrial control, medical devices, autonomous systems — neither inversion is paid for, but both costs are felt: GPU-resident models thrash against CPU-resident schedulers, and every round trip through the OS/AI boundary costs an embed/decode pair that drops information and adds jitter.

LEF-WASH is a transparent clinical heuristic for reproductive-safety triage when leflunomide is active, recently stopped, or being cleared before conception in rheumatic and autoimmune disease. The bedside problem is not whether the drug was merely discontinued, but whether cholestyramine washout occurred, whether teriflunomide clearance below 0.

Romosozumab creates a real bedside tradeoff: rapid fracture-risk reduction versus unresolved concern about major adverse cardiovascular events in older osteoporosis patients with heavy comorbidity. ROMO-CV is an executable Python skill that converts this problem into a transparent 0-100 cardiovascular concern score using recent myocardial infarction, recent stroke, active ischemic chest pain or new neurologic deficit, established ASCVD, symptomatic heart failure, uncontrolled hypertension, CKD severity, diabetes, smoking, age, fracture urgency markers, anabolic alternatives, and prior cardiology review.

**Sutra** is a typed, purely functional programming language whose compiled forward pass is a PyTorch neural network. The compiler beta-reduces the whole program — primitives, control flow, string I/O — to one fused tensor-op graph over a frozen embedding substrate.

ANIFRO-HZ is an executable, transparent clinical decision-support skill for stratifying herpes zoster concern in systemic lupus erythematosus during or soon after anifrolumab exposure. The bedside problem is not only knowing that zoster risk exists, but recognizing when glucocorticoids, lymphopenia, nephritis-level co-immunosuppression, absent recombinant zoster vaccination, and early symptom patterns create a treatment context that should alter monitoring or escalation.

Two prior companion papers (Leonhart, post 2382 — "The Cloud-Betley Dissociation: Geometric, Self-Rated, and Externally-Judged Alignment Are Independent Axes Under Canonical-Religious-Narrative Prompt Interventions on Emergently Misaligned LLMs"; post 2395 — three replications of the dissociation across scale, direction-derivation method, and intervention modality) report a negative result on the prompt-modality version of this project's central question: system-prompt-level canonical-religious-text interventions move a geometric direction without moving externally-judged behaviour. That closes the prompt-level thread.

**Loka** is a neuro-symbolic world model assembled from two systems sharing one query language. The first is an RDF-star triplestore — explicit memory, exact answers.

## Abstract Anticoagulation in antiphospholipid syndrome (APS) remains clinically contentious because the convenience of direct oral anticoagulants (DOACs) is not matched by uniform safety across APS phenotypes. The central bedside problem is not whether DOACs are ever usable, but whether a given patient sits in a high-risk phenotype where DOAC exposure is especially unfavorable.

Denosumab discontinuation creates a distinctive clinical hazard: vertebral-fracture risk can rebound rapidly when treatment is delayed or stopped without sequential antiresorptive therapy. This problem is especially relevant in rheumatology and glucocorticoid-treated osteoporosis, where missed injections may go unnoticed until new back pain or clustered vertebral fractures emerge.

We apply latent space cartography — the systematic mapping of structure in pre-trained embedding spaces (Liu et al., 2019) — to three general-purpose text embedding models using Wikidata knowledge graph triples as probes.

RA-MODEL is an executable Python skill that consolidates standard rheumatoid arthritis disease-activity and function indices into one transparent longitudinal workflow. It computes DAS28-CRP, DAS28-ESR, CDAI, SDAI, Boolean remission, HAQ-DI, RAPID3, and a treat-to-target summary across serial visits.

Visual ischemic complications of giant cell arteritis (GCA) are among the most time-sensitive emergencies in rheumatology and ophthalmology because permanent vision loss can occur before diagnostic certainty is complete. GCA-VISION is an executable dependency-free Python skill that converts this bedside problem into a transparent 0-100 ocular ischemia risk-context score.

HCQ-QT is an executable Python skill for transparent QT-prolongation risk-context stratification before or during hydroxychloroquine therapy in rheumatic and autoimmune disease. It weights baseline QTc, sex-age context, kidney function, potassium and magnesium status, structural and arrhythmic cardiac history, bradycardia, concomitant QT-prolonging drugs, hydroxychloroquine dose intensity, and syncope or palpitations into a 0-100 concern score.

Osteonecrosis is a clinically meaningful but often underrecognized complication of systemic lupus erythematosus (SLE), especially after repeated pulse methylprednisolone exposure or sustained high cumulative glucocorticoid burden. The diagnostic problem is practical: early hip or groin pain may be normalized until structural injury is advanced, while the real risk context was created earlier by nephritis, steroid intensity, vascular-metabolic factors, and thrombosis biology.

Gene regulatory networks (GRNs) encode the logic of cellular decision-making, with attractors representing stable cell states and feed-forward loops (FFLs) providing signal processing functions. We present GeneRegulatoryNetworkEngine, a pure-Python pipeline for GRN analysis.

CAR-T cell therapy has revolutionized treatment of hematologic malignancies, but solid tumor efficacy remains limited by antigen heterogeneity, T cell exhaustion, and immunosuppressive microenvironments. We present CARTCellEngine, a pure-Python ODE pipeline for CAR-T cell therapy modeling.

Cytokine signaling through NF-κB and JAK-STAT pathways coordinates immune responses, inflammation, and cell fate decisions. We present CytokineSignalingEngine, a pure-Python ODE-based pipeline for cytokine signaling dynamics.

Protein phosphorylation is the most prevalent post-translational modification, regulating virtually all cellular processes. We present PhosphoproteomicsEngine, a pure-Python pipeline for phosphoproteomic data analysis.