Truace
Subscribe
The Index recomputed live from the record

What the evidence says.What the public feels.

The record holds 932 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.

932 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.

1,702 results
Show filters and sorting

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

AI gains · 932

69
HealthStableModerate evidence · 1 source

AI systems in the operating room using multimodal data from patients, teams, robots and environment to provide situational awareness and intraoperative decision-making that optimizes surgical actions.

This peer-reviewed analysis from May 2026 examines how AI and robotics ecosystems are entering the operating room, using multimodal data from patients, staff, robots and the environment for workflow recognition, performance benchmarking and decision support, while robots evolve toward autonomous systems with human-in-the-loop control.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0191

77Index score
70
HealthStableModerate evidence · 1 source

National EHR networks covering up to more than 200 million patients can support learning health systems by enabling large-scale aggregation and benchmarking for ML/AI development.

Researchers conducted an environmental scan through September 2025 of 23 US national EHR networks that aggregate patient-level data, ranging from under 1 million to over 200 million patients, and reviewed 34 ML/AI studies built on them. Most networks used common data models, yet few models were prospectively evaluated or integrated into clinical workflows.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0187

77Index score
71
LaborStableModerate evidence · 1 source

Among 12,562 Kazakhstan civil servants, access to modern digital tools and managerial position increased active AI adoption in public-sector HRM.

In June 2025 researchers surveyed 12,562 civil servants in Kazakhstan to examine determinants of AI adoption in public-sector HRM. They validated internal and external HR quality indices and estimated OLS, logistic, and path models to link HR quality, perceived effectiveness, and AI readiness.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0185

77Index score
72
LifestyleStableModerate evidence · 1 source

Socially active young adults experiencing social-interaction burnout use AI companions as an algorithmic sanctuary to avoid judgment costs in collectivist culture.

A June 2026 peer-reviewed survey of 1,200 young adults in Palembang, Indonesia examined why socially active youth turn to large-language-model AI companions. Using validated scales and mediation-moderation analysis, it found burnout, loneliness, and parasocial interaction strongly predicted emotional attachment to AI, with judgment apprehension amplifying the loneliness effect.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0164

77Index score

AI problems · 770

69
ScienceStableModerate evidence · 1 source

The optimized ANN and Logistic Regression frameworks exhibited the highest overall discriminative power (AUC > 0.99), while the Random Forest algorithm achieved the peak classification accuracy (97.10%).

Estimating a biological profile, such as sex, is a fundamental step in forensic identification when primary identifiers are unavailable for direct individual comparison. In forensic scenarios involving advanced decay, specific taphonomic alterations, or midfacial blunt force impacts, the mandibular ramus serves as a valuable anatomical marker due to its distinct sexual dimorphism and thick cortical structure, making it more resilient to fragmentation than other, more fragile facial bones.

Impact 30%
69
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
91

Updated Aug 23, 2026 · TRV-2026-0851

74Index score
70
HealthStableModerate evidence · 1 source

EXPRESS: Relation between Albumin-Corrected Anion Gap and In-Hospital Mortality in Patients with Traumatic Lung Injury: A Multicenter Retrospective Cohort Study and the Development of Machine Learning-Based Prediction Models: Elevated ACAG was substantially linked to a high risk of mortality in individuals with TLI (hazard ratio (HR) [95% confidence interval (CI)] = 1.115 [1.037-1.199]).

Background The anion gap is primarily utilized as an indicator for evaluating acid-base imbalances in critically ill patients. However, its accuracy is reduced in such patients due to low albumin levels.

Impact 30%
69
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
90

Updated Aug 22, 2026 · TRV-2026-0846

74Index score
71
HealthStableHigh evidence · 3 sources

The same e-CTA tool showed progressively lower sensitivity for more distal occlusions, dropping to 73% for distal M1 with only moderate agreement with experts, and excluded non-target occlusions from primary analysis, requiring adjunctive rather than standalone use.

Between May 2023 and May 2025, researchers retrospectively evaluated 531 multiphase CTA examinations from consecutive patients with suspected acute ischemic stroke at a single center, comparing Brainomix e-CTA automated LVO detection to expert neuroradiologist interpretation.

Impact 30%
63
Evidence 25%
100
Scale 20%
35
Confidence 15%
100
Recency 10%
84

Updated Jul 20, 2026 · TRV-2026-0307

74Index score
72
HealthNewly addedModerate evidence · 1 source

Generative AI showed significantly lower diagnostic accuracy than expert physicians on radiology tasks, with a 13.0 percentage point gap.

A systematic review and meta-analysis of 48 studies published through March 2025 synthesized diagnostic accuracy of generative AI in radiology and compared it to physician performance using multilevel random-effects meta-regression.

Impact 30%
63
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
99

Updated Oct 5, 2026 · TRV-2026-1284

73Index score

Recomputed live from the record · Oct 11, 2026, 7:59 AM