A Machine Learning Framework for Turbofan Health Estimation via Inverse Problem Formulation explores A machine learning framework for turbofan health estimation using a new dataset and self-supervised learning to address the ill-posed inverse problem.. Commercial viability score: 5/10 in MLOps.
Use This Via API or MCP
This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Page Freshness
Canonical route: /paper/a-machine-learning-framework-for-turbofan-health-estimation-via-inverse-problem-formulation
This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.
Agent Handoff
Canonical ID a-machine-learning-framework-for-turbofan-health-estimation-via-inverse-problem-formulation | Route /paper/a-machine-learning-framework-for-turbofan-health-estimation-via-inverse-problem-formulation
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/a-machine-learning-framework-for-turbofan-health-estimation-via-inverse-problem-formulationMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.08460"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "A Machine Learning Framework for Turbofan Health Estimation via Inverse Problem Formulation",
"normalized_query": "2604.08460",
"route": "/paper/a-machine-learning-framework-for-turbofan-health-estimation-via-inverse-problem-formulation",
"paper_ref": "a-machine-learning-framework-for-turbofan-health-estimation-via-inverse-problem-formulation",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Paper proof page receipt window
/buildability/a-machine-learning-framework-for-turbofan-health-estimation-via-inverse-problem-formulation
Subject: A Machine Learning Framework for Turbofan Health Estimation via Inverse Problem Formulation
Verdict
Watch
Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
Research neighborhood
Interactive graph renders after load.
Preparing verified analysis
Dimensions overall score 5.0
No public claim map is available for this paper yet.
Visual citation anchors from the paper document graph.
This equation captures one of the core mathematical components of the system. SMAPE 0.24 ± 0.21 0.19 ± 0.20 0.30 ± 0.26 0.05 ± 0.13 0.09 ± 0.14 0.18 ± 0.21 0.19 ± 0.19 0.16 ± 0.18 0.24 ± 0.22 0.33 ±
Page and bbox are available; crop image is pending.
Owned Distribution
Get the weekly shortlist of commercializable papers, benchmark movers, and proof receipts that matter for product execution.
References are not available from the internal index yet.
Receipt path
/buildability/a-machine-learning-framework-for-turbofan-health-estimation-via-inverse-problem-formulation
Paper ref
a-machine-learning-framework-for-turbofan-health-estimation-via-inverse-problem-formulation
arXiv id
2604.08460
Generated at
2026-04-10T17:40:46.856Z
Evidence freshness
stale
Last verification
2026-04-10T17:40:46.856Z
Sources
3
References
0
Coverage
50%
Lineage hash
ed5d2ee314ad87d50d8cc67a8938cb70010df00e1a5c72755a091276a890f636
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Pending verification refs / 3 sources / Verification pending
repo_url
references
This equation captures one of the core mathematical components of the system. SMAPE 0.20 ± 0.25 0.15 ± 0.23 0.28 ± 0.25 0.05 ± 0.15 0.07 ± 0.16 0.12 ± 0.21 0.17 ± 0.22 0.12 ± 0.21 0.22 ± 0.24 0.30 ±
Page and bbox are available; crop image is pending.
This equation captures one of the core mathematical components of the system. SMAPE 0.12 ± 0.22 0.09 ± 0.19 0.27 ± 0.24 0.04 ± 0.14 0.05 ± 0.16 0.08 ± 0.19 0.16 ± 0.21 0.07 ± 0.19 0.22 ± 0.23 0.28 ±
Page and bbox are available; crop image is pending.
No public competitor map is available for this paper yet.