Standardized Intermediate Payload (SIP)

• Standardized Intermediate Payload (SIP) is a unified, decoupled JSON output that packages clinical AI results and structured bypass metadata to support healthcare interoperability.
• It creates a strict architectural boundary between LCA internal orchestration and external systems, ensuring invariant payload structure despite model changes.
• SIP encapsulates failure semantics, supplementary data requests, and traceable input provenance to enable robust, auditable clinical diagnostics.

to=arxiv_search 彩神争霸安卓 皇轩json {"query":"(Marrakchi et al., 7 Jul 2026) Standardized Intermediate Payload Large Cancer Assistant", "max_results": 5} Standardized Intermediate Payload (SIP) is the sole external output of the Large Cancer Assistant (LCA), produced by the Large Cancer Wordings Module (LCWM) after preprocessing, routing, diagnostic or remedy execution, and failure handling. Formally, the paper defines it as

$$\text{SIP} = (\text{text\_output}, \text{structured\_bypass}),$$

combining a natural-language narrative with machine-readable structured content. In the LCA framework, SIP functions as a strict architectural boundary between internal orchestration logic and downstream systems, including future Electronic Medical Record interoperability layers, while downstream systems consume the SIP without interacting with any internal LCA module (Marrakchi et al., 7 Jul 2026).

1. Definition and architectural role

The defining purpose of SIP is architectural decoupling. The LCA paper describes it as a unified Standardized Intermediate Payload, a decoupled, proprietary JSON payload, and the sole external output of the framework. Its role is to isolate the core AI execution from volatile hospital IT infrastructures, so that changes to HL7 FHIR versions, database schemas, or institutional IT systems do not require modification of any module upstream of the LCWM (Marrakchi et al., 7 Jul 2026).

This boundary is deliberately strict. SIP is not presented as a direct hospital database write, nor as a finalized interoperability standard. Appendix E of the paper states that the internal structure of SIP is not specified at the framework level and is instead the subject of subsequent interoperability work, specifically HL7 FHIR mapping. The appendix simultaneously defines SIP as the output of LCWM and frames it as the architectural boundary between the LCA framework and downstream systems. A central implication is that the framework separates orchestration from interoperability rather than treating them as a single software problem (Marrakchi et al., 7 Jul 2026).

2. Position within the LCA formalism

The LCA is formalized as a 7-tuple:

$$\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$$

Within this formalism, SIP is not itself one of the seven tuple elements. It is the terminal output generated by the seventh element, $f_{LCW}$, after the preceding modules have standardized data, selected protocols, and produced protocol-specific outputs (Marrakchi et al., 7 Jul 2026).

The paper reconstructs the internal dataflow as a directed sequence

$$\text{DPM} \rightarrow \text{CSM} \rightarrow \{\text{LCDM}, \text{LCRM}\} \rightarrow \text{LCWM} \rightarrow \text{SIP},$$

where DPM denotes the Data Preprocessing Module, CSM the Cancer Switching Module, LCDM the Large Cancer Diagnostic Module, LCRM the Large Cancer Remedy Module, and LCWM the Large Cancer Wordings Module. The LCWM mapping is given as

$$f_{LCW}\!\Bigl(\hat{P},\; \{\tilde{y}_{LCD}^{(k)}\}_{p_k \in \hat{P}_{LCD}},\; \{\tilde{y}_{LCR}^{(k)}\}_{p_k \in \hat{P}_{LCR}},\; \mathcal{D}_{out}\Bigr) = \text{SIP}.$$

In prose, SIP therefore packages the routing decision $\hat{P}$, the protocol-level diagnostic outputs, the protocol-level remedy outputs, and the bypassed preprocessed history $\mathcal{D}_{out}$ into a single external contract (Marrakchi et al., 7 Jul 2026).

The routing layer is also formalized. In the V2 configuration of the CSM, protocol activation is threshold based:

$$\hat{P}(e) = \bigl\{p_k \in \mathcal{P} \;:\; h(e)_k \geq \tau\bigr\},$$

with

$$R_{V2}(e) = \begin{cases} \hat{P}(e) & \text{if } \hat{P}(e) \neq \varnothing \ \bot & \text{if } \hat{P}(e) = \varnothing. \end{cases}$$

This matters for SIP because the payload must represent both successful protocol activations and CSM-level failure states (Marrakchi et al., 7 Jul 2026).

3. Entry Theory, multimodal standardization, and structured bypass

The formal substrate beneath SIP is Entry Theory. The paper represents any modality as a signal on a structured domain,

$x \in \mathcal{C}^{\Omega},$

with a characterized entry defined as

$$\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$$0

where the medical signature is

$$\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$$1

Here $$\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$$2 denotes provenance, $$\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$$3 usage, and $$\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$$4 epistemic certainty. The paper explicitly states that the computer-science axis $$\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$$5 and the medical axis $$\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$$6 are mutually independent (Marrakchi et al., 7 Jul 2026).

Clinical input is modeled as an ordered history:

$$\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$$7

The Data Preprocessing Module standardizes these entries through provenance-specific preprocessing and recomposition. The direct significance for SIP is that the payload does not simply carry final predictions; it carries a structured bypass of the preprocessed history, preserving references and signatures that record how inputs entered the system (Marrakchi et al., 7 Jul 2026).

The paper’s proof-of-concept schema makes this concrete. SIP includes a header, patient and run references, DPM profile information, and entry_refs[] records containing acquisition index, external identifier, and the medical signature $$\sigma = (\rho,u,\kappa)`. The paper also notes that heavy input content is not embedded in the payload; instead, SIP carries entry references and provenance-linked structure. This makes the structured bypass more than a logging convenience: it is the mechanism by which the orchestration layer exposes standardized, traceable clinical history without coupling itself to downstream storage conventions (<a href="/papers/2607.06531" title="" rel="nofollow" data-turbo="false" class="assistant-link" x-data x-tooltip.raw="">Marrakchi et al., 7 Jul 2026</a>).</p> <h2 class='paper-heading' id='algorithmic-impermeability-and-invariant-payload-structure'>4. Algorithmic Impermeability and invariant payload structure</h2> <p>A central theoretical property of SIP is its role in enforcing <a href="https://www.emergentmind.com/topics/algorithmic-impermeability" title="" rel="nofollow" data-turbo="false" class="assistant-link" x-data x-tooltip.raw="">Algorithmic Impermeability</a>. The paper defines this principle as requiring orchestration logic to remain strictly independent of underlying black-box AI models, provided those models satisfy the declared interface contracts. SIP is the observable boundary through which this independence is tested (<a href="/papers/2607.06531" title="" rel="nofollow" data-turbo="false" class="assistant-link" x-data x-tooltip.raw="">Marrakchi et al., 7 Jul 2026</a>).</p> <p>The key formal statement is Proposition 2. Let$$\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$8 denote the projection of the SIP onto its orchestration-structural component, retaining the activation set $\text{LCA} = \bigl(\mathcal{E},\;\mathcal{P},\;f_{DP},\;f_{CS},\;f_{LCD},\;f_{LCR},\;f_{LCW}\bigr).$9, the per-protocol routing decisions, the set of protocols emitting $f_{LCW}$0, and the SIP schema, while discarding inference content and generated text. Then

$f_{LCW}$1

This means that replacing one conformant model with another may change predicted content but must not change the orchestration-structural projection of the payload (Marrakchi et al., 7 Jul 2026).

The same section introduces an implementation corollary: machine-learning model identities are strictly excluded from the SIP. The stated reason is that exposing such identities would create downstream dependencies and thereby violate the impermeability guarantee. The paper therefore assigns SIP a dual function: it is both a transport object for outputs and a formal device for preventing downstream coupling to model-specific internals (Marrakchi et al., 7 Jul 2026).

The proof-of-concept directly evaluated this property in Scenario 2. Two diagnostically distinct stubs satisfying the same interface contract were swapped, and the results showed $f_{LCW}$2-equality of 100% with content difference of 100%. The reported result is not merely that predictions changed; it is that the structural projection of SIP remained invariant under model replacement (Marrakchi et al., 7 Jul 2026).

5. Failure semantics, Supplementary Data Requests, and safety

SIP is also the framework’s universal failure envelope. Design principle D1 states that the LCWM invariably produces a SIP: regardless of success or failure, the top-level payload structure remains a SIP. If a module failure occurs through emission of $f_{LCW}$3, the resulting Supplementary Data Request (SDR) is embedded within the SIP rather than replacing it with another payload type (Marrakchi et al., 7 Jul 2026).

The paper distinguishes two SDR forms. A top-level SDR is defined as

$f_{LCW}$4

while a protocol-level SDR is

$f_{LCW}$5

The first is used when the CSM emits $f_{LCW}$6 and no protocol is activated; the second is used when a specific protocol branch fails at the LCDM or LCRM stage. In both cases, the request is carried inside the SIP narrative and structured protocol outputs (Marrakchi et al., 7 Jul 2026).

The failure model further separates $f_{LCW}$7 from <code>CODE_FAIL</code>. The paper defines$f_{LCW}$$8 as an input or precondition failure that should halt processing for that <a href="https://www.emergentmind.com/topics/scope" title="" rel="nofollow" data-turbo="false" class="assistant-link" x-data x-tooltip.raw="">scope</a> and generate an SDR. By contrast, <code>CODE_FAIL</code> denotes an internal inference failure on otherwise valid input and must not masquerade as missing data. This distinction gives SIP an audit function: downstream systems can determine whether an abnormal state was caused by absent evidence or by internal model failure (<a href="/papers/2607.06531" title="" rel="nofollow" data-turbo="false" class="assistant-link" x-data x-tooltip.raw="">Marrakchi et al., 7 Jul 2026</a>).</p> <p>Scenario 3 of the proof-of-concept evaluated this safety property. Under injected anomalies involving corrupted CT and missing required modality, the system achieved 100$$f_{LCW}$9, correct source attribution, emitting an SDR, and avoiding a generic request. The paper summarizes the intended guarantee as “No failure is silent,” and SIP is the structure through which that guarantee becomes externally visible (Marrakchi et al., 7 Jul 2026).

6. Validation, schema content, and current limitations

The proof-of-concept validated the SIP-oriented orchestration logic across four technical scenarios. In Scenario 1, all payloads were schema-valid and completion rate was 100%. The reported module latencies were

• $\text{DPM} \rightarrow \text{CSM} \rightarrow \{\text{LCDM}, \text{LCRM}\} \rightarrow \text{LCWM} \rightarrow \text{SIP},$0 ms,
• $\text{DPM} \rightarrow \text{CSM} \rightarrow \{\text{LCDM}, \text{LCRM}\} \rightarrow \text{LCWM} \rightarrow \text{SIP},$1 ms,
• $\text{DPM} \rightarrow \text{CSM} \rightarrow \{\text{LCDM}, \text{LCRM}\} \rightarrow \text{LCWM} \rightarrow \text{SIP},$2 ms,
• $\text{DPM} \rightarrow \text{CSM} \rightarrow \{\text{LCDM}, \text{LCRM}\} \rightarrow \text{LCWM} \rightarrow \text{SIP},$3 ms,
• $\text{DPM} \rightarrow \text{CSM} \rightarrow \{\text{LCDM}, \text{LCRM}\} \rightarrow \text{LCWM} \rightarrow \text{SIP},$4 ms,
• total $\text{DPM} \rightarrow \text{CSM} \rightarrow \{\text{LCDM}, \text{LCRM}\} \rightarrow \text{LCWM} \rightarrow \text{SIP},$5 ms,

with orchestration-only cost, defined as DPM plus CSM plus LCWM, described as about 0.04 ms and negligible compared with production inference (Marrakchi et al., 7 Jul 2026).

The same proof-of-concept showed that SIP can aggregate multiple protocol branches. In Scenario 4, with $\text{DPM} \rightarrow \text{CSM} \rightarrow \{\text{LCDM}, \text{LCRM}\} \rightarrow \text{LCWM} \rightarrow \text{SIP},$6, branch independence was 100%, composite SIP schema validity was 100%, and protocol-output cardinality equal to 2 was also 100%. This establishes that the payload can encode multiple concurrent protocol executions without structural collapse (Marrakchi et al., 7 Jul 2026).

The paper’s annotated schema describes a payload containing header metadata, input provenance, CSM execution trace, optional CSM-level SDR, per-protocol outputs, interpretability references such as grad_cam_ref and attention_map_ref, and the LCWM narrative. At the same time, the paper explicitly cautions that SIP internal structure is not specified at the framework level. The JSON representation should therefore be understood as a proof-of-concept implementation specification rather than a final universal standard (Marrakchi et al., 7 Jul 2026).

Several limitations remain explicit. The proof-of-concept uses synthetic data and stubs rather than deployed clinical models. V2 routing was not empirically validated. Full HL7 FHIR translation is deferred to future work. Remedy and SDR templates require maintenance, and the current natural-language generation is English-centric. The paper therefore presents SIP as a formal and implementable boundary abstraction, but not yet as a completed interoperability standard (Marrakchi et al., 7 Jul 2026).

7. Terminological ambiguity across arXiv literature

The acronym “SIP” is heavily overloaded in technical literature, and contextual disambiguation is necessary. In the LCA paper it denotes Standardized Intermediate Payload (Marrakchi et al., 7 Jul 2026), but in wireless communications it may denote superimposed pilots. For example, “Channel-Aware Deep Learning for Superimposed Pilot Power Allocation and Receiver Design” uses SIP for superimposed pilot schemes and introduces CaSIP for pilot-data power allocation and receiver design (Gu et al., 13 Oct 2025). A related integrated sensing and communication paper likewise studies hybrid waveforms with deterministic pilots and random data payloads, while explicitly identifying SIP as superimposed pilot transmission (Xie et al., 16 Jan 2026).

In medical robotics, SIP can instead mean standardized imaging plane. “Guiding the Last Centimeter: Novel Anatomy-Aware Probe Servoing for Standardized Imaging Plane Navigation in Robotic Lung Ultrasound” defines SIP as the 2D B-mode ultrasound slice that cuts the target anatomy from a certain orientation such that necessary diagnostic information can be acquired (Ma et al., 2024). In networking and telephony, SIP commonly denotes the Session Initiation Protocol, as in work on TCP-based SIP server overload control (Shen et al., 2010).

A related but distinct notion of an intermediate encapsulation layer appears in 5G simulation research on the Service Data Adaptation Protocol. That work describes SDAP as a user-plane sublayer between IP and PDCP carrying standardized flow metadata such as QFI, which is close to an intermediate payload handling mechanism, but it is not called Standardized Intermediate Payload (Seliem et al., 18 Aug 2025).

SIP usage	Domain	Example
Standardized Intermediate Payload	Clinical AI orchestration	LCA (Marrakchi et al., 7 Jul 2026)
Superimposed pilot	Wireless communications	CaSIP (Gu et al., 13 Oct 2025)
Standardized imaging plane	Robotic ultrasound	Lung ultrasound navigation (Ma et al., 2024)

This terminological diversity suggests that the meaning of SIP is inseparable from system context. Within the LCA framework, however, the term has a precise and formalized sense: a stable, structured boundary object that decouples multimodal orchestration and black-box inference from downstream healthcare IT while preserving provenance, failure semantics, and schema-level invariance (Marrakchi et al., 7 Jul 2026).