From Anomaly to Candidate Technosignature: The Threshold Problem of the Loeb Scale

TL;DR

This paper examines how thresholds in the Loeb Scale influence scientific inquiry into potential technosignatures, proposing a nuanced epistemic status to guide research under uncertainty.

Contribution

It offers a philosophical analysis of the threshold concept in the Loeb Scale and suggests a structured scientific commitment for candidate technosignatures.

Findings

Candidate technosignature status is an intermediate epistemic state.

Historical cases show discovery delays due to paradigms and institutional factors.

AI can assist in anomaly detection and prioritization once candidate status is established.

Abstract

Recent work on the Loeb Scale has provided astronomy a structured framework for assessing anomalous interstellar objects, including a quantitative mapping of a classification ranking, its evolution with the addition of data, and a broader observational strategy for firming its verdict. What remains unclear is the epistemic and methodological meaning of the threshold built into that framework. Here we argue that the central philosophical issue is no longer whether astronomy can define such a threshold, but how a threshold already in place should regulate scientific inquiry under uncertainty. We suggest that candidate technosignature status, such as Level 4 on the Loeb Scale, should be understood as an intermediate epistemic status: stronger than permissive openness, weaker than confirmation, yet sufficient to justify methodological escalation. The argument proceeds in three steps. First, it reconstructs the recent philosophical debate through the work of Lomas, Lane, and Cowie. Second, it turns to historical cases discussed by Kaplan (2026) to show that important discoveries are often delayed not only by weak evidence, but also by paradigms, prestige, and institutional filtering. Third, it interprets candidate status as a form of structured scientific commitment under uncertainty, one that justifies intensified observation, broader hypothesis management, and more deliberate allocation of attention and resources without licensing belief in artificial origin. The paper concludes by arguing that AI should not be the arbitrator in deducing an extraterrestrial origin, but can support the detection, comparison, and prioritization of anomalies once a candidate status has been formally recognized.