− HEALTH The FDA received a malfunction report involving Inogen one g5 oxygen concentrator, made by Inogen, Inc.. Rece…+ HEALTH Objective We systematically evaluated the diagnostic performance of artificial intelligence (AI)-assisted int…− HEALTH BackgroundFall-related injuries in older adults remain a major health concern, contributing to functional dep…− CLIMATE Background Chronic inflammation is a major driver of cardiovascular diseases, but mechanisms linking systemic…− HEALTH Disease macroecology relies on large, complex datasets to understand the biotic and abiotic factors shaping p…− HEALTH Background National Surgical Quality Improvement Program (NSQIP) data collection depends on labor-intensive m…+ HEALTH ObjectivePerceptual evaluation by speech-language pathologists (SLPs) is essential for initial evaluation of…− HEALTH Background Heart failure with preserved ejection fraction is a heterogeneous syndrome, and comorbid obstructi…
TruaceTracing the truth around AISaturday, September 19, 2026
Subscribe
TRV-2026-1142Certified recordPeer-reviewed

Can't see the forest for the trees? Statistical considerations for disease macroecology

Disease macroecology relies on large, complex datasets to understand the biotic and abiotic factors shaping parasite distributions and emerging infectious disease risk. These datasets span local to global host-parasite interactions and often integrate diverse host or parasite traits across evolutionary histories. Selecting appropriate statistical approaches requires first asking key questions about the study system: How well is the system understood? How important is predictor accuracy? How much bias is present…

Health · P Space — documented harm · certified 2026-09-19 · v1 · article view · machine-readable

Current reading — problem

Can't see the forest for the trees? Statistical considerations for disease macroecology: Disease macroecology relies on large, complex datasets to understand the biotic and abiotic factors shaping parasite distributions and emerging infectious disease risk.

Evidence

Reader signal

How should this claim be treated?

Cite this record

Truvace Impact Record TRV-2026-1142, v1: “Can't see the forest for the trees? Statistical considerations for disease macroecology.” Truvace, 2026-09-19. /record/TRV-2026-1142 (accessed at citation time). sha256 b562b161784bacee…

Calibration history

Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.

  1. Certifiedv1b562b161784b…

    Certified into the record

Verify this record
How to verify without trusting this page

Fetch the canonical text of any version from /api/record/TRV-2026-1142 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.