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This paper studies observability and identifiability in coherence-constrained backward reconstruction frameworks related to the Synthesis & Estimation Architecture (SEA), focusing on how uncertainty classes behave when extending Earth-based methods to planetary and astrophysical reconstruction. Using a framework that identifies residual uncertainty classes and tests their measurability under different observational regimes, the authors find eight uncertainty classes specific to space/planetary contexts and determine which can be narrowed statistically by accumulating SEA reconstructions across many systems versus which remain structurally irreducible even at large population sizes. The paper explicitly notes it is a preprint and that results may be preliminary, and it positions itself as part of a broader series developing SEA for observability-limited inference across domains. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.
Abstract
Coherence-constrained backward reconstruction frameworks, such as the Synthesis & Estimation Architecture (SEA), reduce admissible historical trajectories by enforcing global consistency across heterogeneous observables. While powerful in Earth system applications, their extension to planetary and astrophysical contexts raises distinct questions of observability and identifiability. Here we examine whether residual uncertainty classes identified in Earth-based SEA applications admit measurable analogs in space, and whether accumulation of SEA reconstructions across many systems can progressively constrain these uncertainties. We identify eight residual uncertainty classes specific to space and planetary systems, evaluate their measurability under current and foreseeable observational regimes, and distinguish which classes can be narrowed statistically through population-level accumulation versus those that remain structurally irreducible even at large N. This work provides a principled framework for interpreting SEA outputs in space contexts and clarifies which uncertainties reflect fundamental observability limits. This paper forms part of a broader series developing the Synthesis & Estimation Architecture (SEA) as a domain-general framework for coherence-constrained reconstruction and observability-limited inference across Earth, planetary, and astrophysical systems.
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Observability Limits in Coherence-Constrained Planetary Reconstruction: The Role of Population Accumulation | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 13 February 2026 V1 Latest version Share on Observability Limits in Coherence-Constrained Planetary Reconstruction: The Role of Population Accumulation Author : Peter Brunzelle 0009-0005-7109-6745 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177100811.10091485/v1 96 views 78 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Coherence-constrained backward reconstruction frameworks, such as the Synthesis & Estimation Architecture (SEA), reduce admissible historical trajectories by enforcing global consistency across heterogeneous observables. While powerful in Earth system applications, their extension to planetary and astrophysical contexts raises distinct questions of observability and identifiability. Here we examine whether residual uncertainty classes identified in Earth-based SEA applications admit measurable analogs in space, and whether accumulation of SEA reconstructions across many systems can progressively constrain these uncertainties. We identify eight residual uncertainty classes specific to space and planetary systems, evaluate their measurability under current and foreseeable observational regimes, and distinguish which classes can be narrowed statistically through population-level accumulation versus those that remain structurally irreducible even at large N. This work provides a principled framework for interpreting SEA outputs in space contexts and clarifies which uncertainties reflect fundamental observability limits. This paper forms part of a broader series developing the Synthesis & Estimation Architecture (SEA) as a domain-general framework for coherence-constrained reconstruction and observability-limited inference across Earth, planetary, and astrophysical systems. Supplementary Material File (observability_limits_in_coherence_constrained_planetary_reconstruction__the_role_of_population_accumulation (2).pdf) Download 290.70 KB Information & Authors Information Version history V1 Version 1 13 February 2026 Copyright This work is licensed under a Creative Commons Attribution 4.0 International License Keywords coherence-constrained inference ensemble reconstruction identifiability inverse problems observability limits planetary system architecture Authors Affiliations Peter Brunzelle 0009-0005-7109-6745 [email protected] Independent Researcher View all articles by this author Metrics & Citations Metrics Article Usage 96 views 78 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Peter Brunzelle. Observability Limits in Coherence-Constrained Planetary Reconstruction: The Role of Population Accumulation. Authorea . 13 February 2026. DOI: https://doi.org/10.22541/au.177100811.10091485/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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