Truace
Subscribe
The Index recomputed live from the record

What the evidence says.What the public feels.

The record holds 929 sourced gains and 770 sourced problems, averaging 68 and 66 on the index score. Readers have logged 22 public signals on the Pulse, which is kept apart and never counted as evidence.

929 gains
770 problems
Every sourced claim in the Index, one square each, shaded by the strength of its evidence. High Moderate Emerging

Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.

1,699 results
Show filters and sorting

Download every matching row, not just this page:Export CSVExport JSON

AI gains · 929

1
CrimeStableModerate evidence · 1 source

A SnSe/SnO2 p-n heterojunction single-sensor virtual electronic nose using a PCA-KNN framework enables room-temperature, non-contact detection and classification of volatile sulfur compounds released during methamphetamine production and trafficking, with high response to low-concentration H2S and 96.7% accuracy for H2

As of the September 2026 publication, researchers reported a SnSe/SnO2 p-n heterojunction device operated as a single-sensor virtual electronic nose for volatile sulfur compounds associated with illicit methamphetamine trafficking. The work combined material synthesis, DFT analysis of adsorption energetics, and a PCA-KNN model built on 12-dimensional features from response curves to identify six VSC systems.

Impact 30%
69
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
94

Updated Sep 8, 2026 · TRV-2026-1015

84Index score
2
HealthStableModerate evidence · 1 source

An interpretable multi-instance learning method for accurate differentiation of malignant and benign laryngeal lesions in laryngoscopy: Results IMIL-Net achieved the highest diagnostic performance, with a mean area under the curve (AUC) of 0.975 (95% CI 0.959-0.991), accuracy of 0.915 (95% CI 0.883-0.947), sensitivity of 0.876 (95% CI 0.803-0.949), and specificity of 0.945 (95% CI 0.910-0.980).

Background Laryngeal cancer is a significant global health issue with high mortality, and early diagnosis is critical for survival. Developing accurate diagnostic models for laryngoscopy can reduce potential repeated biopsies and lessen the patient burden, representing an urgent clinical need.

Impact 30%
69
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
90

Updated Aug 22, 2026 · TRV-2026-0850

84Index score
3
HealthStableModerate evidence · 1 source

Systematic review of 35 studies found classical AI models for bipolar disorder achieved pooled AUC 0.80 for long-term maintenance response and 85%-97% accuracy for safety and dose optimization.

A PRISMA-guided systematic review of 35 studies examined classical AI for treatment optimization in adult bipolar disorder across five outcomes: acute response, long-term maintenance, relapse/readmission, safety/dose, and brain aging/phenotyping. By the July 2026 publication date, pooled performance ranged from modest for acute response (AUC 0.68) to moderate-to-high for maintenance (AUC 0.80) and high accuracy for safety/dose (85%-97%).

Impact 30%
69
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
85

Updated Jul 22, 2026 · TRV-2026-0511

83Index score
4
ClimateStableModerate evidence · 1 source

Adopting best practices for AI servers in the USA could cut projected carbon emissions by up to 73% and water footprints by up to 86% between 2024 and 2030.

Published November 10 2025 in Nature Sustainability, the study models the sustainability implications of rapidly expanding generative AI server installations across the United States, projecting annual water and carbon footprints through 2030 and testing mitigation options.

Impact 30%
69
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
84

Updated Jul 22, 2026 · TRV-2026-0474

83Index score

AI problems · 770

1
LifestyleStableModerate evidence · 1 source

Finally, we demonstrate how Microbial Community-scale Metabolic Modeling (MCMM) and multimodal machine learning mechanistically couple specific dietary inputs with unique microbiome responses, yielding up to 95% diagnostic accuracy in differentiating diet-responsive metabolic states and individualized postprandial glycemic outcomes.

Precision nutrition on a global scale necessitates an understanding of food not as static collections of so-called macronutrients but rather as dynamic and heterogeneous biochemical matrices. These complex non-linear interactions between food composition, gastrointestinal digestion and the human microbiome are difficult to capture using traditional empirical experimental methods.

Impact 30%
69
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
96

Updated Sep 22, 2026 · TRV-2026-1171

84Index score
2
HealthStableModerate evidence · 1 source

A two-layer DNN is trained using the Levenberg-Marquardt algorithm with a 70%-15%-15% data split.

The rapid spread of infectious diseases can lead to substantial casualties worldwide, with the greatest impact on economically disadvantaged and resource-deficient nations. The widespread transmission of infection disrupts social life and economic activities, amplifying their impact beyond the public health system.

Impact 30%
69
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
96

Updated Sep 21, 2026 · TRV-2026-1159

84Index score
3
HealthNewly addedModerate evidence · 1 source

Chatbots failed to answer 4.2% of interactions, received negative ratings for insufficient detail, and showed only 45% full guideline adherence with weak agreement between LLM and physician assessments.

Researchers co-developed ten disease-specific chatbots grounded in German rheumatology guidelines and deployed them through 13 rheumatology centres and six patient organisations from September 2025 to January 2026. They analyzed 6291 user questions, 2671 user ratings of responses, and 602 questionnaire responses, plus a six-dimensional LLM-as-a-judge assessment compared with rheumatologist ratings in subsets.

Impact 30%
63
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
99

Updated Oct 6, 2026 · TRV-2026-1292

83Index score
4
HealthStableModerate evidence · 1 source

Despite high awareness, most Chinese oncology professionals have not practically integrated medical AI, with only 17.7% reporting both hearing of and using it and 67.7% hearing but never using it.

A nationwide cross-sectional survey of 610 oncology professionals in China (188 physicians, 422 nurses) examined attitudes toward medical AI using the UTAUT model. Only 17.7% had both heard of and used medical AI while 67.7% had heard but never used it, indicating an awareness-usage gap.

Impact 30%
63
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
91

Updated Aug 27, 2026 · TRV-2026-0906

82Index score

Recomputed live from the record · Oct 11, 2026, 12:34 AM