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

82
SportsStableHigh evidence · 5 sources

Machine learning models demonstrated promising accuracy for sport applications including action recognition, injury prediction and prevention, and athlete selection, offering opportunities for performance enhancement and decision-making.

A scoping review published May 25, 2026 examined 270 peer-reviewed studies from 2002 to 2024 on machine learning in sport. It found applications across 12 subject areas, most frequently computer science, biomechanics, and sport psychology, with common uses in action recognition, injury prediction/prevention, and athlete selection/talent identification.

Impact 30%
49
Evidence 25%
100
Scale 20%
60
Confidence 15%
100
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0186

75Index score
83
LaborStableHigh evidence · 5 sources

Integration of blockchain and AI in accounting improves audit quality, enhances transparency and data reliability, and reduces operational costs while automating routine tasks.

Published May 8 2026, this peer-reviewed study examined how blockchain and artificial intelligence are changing accounting, auditing, financial reporting, and accounting education. Using questionnaires from Chartered Accountants and audit firm professionals, it found that blockchain's immutable transparent ledger and AI automation can improve data reliability, enable real-time auditing, and reduce fraud and operational costs.

Impact 30%
49
Evidence 25%
100
Scale 20%
60
Confidence 15%
100
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0169

75Index score
84
CrimeNewly addedModerate evidence · 1 source

Peer-reviewed synthesis finds AI-enabled cybersecurity defenses reduce successful breaches by up to 30% in real-world deployment contexts.

On 2025-09-08, a peer-reviewed review in Computers synthesized 256 publications to bridge computer science and cybersecurity advances in explainable AI, automated development, and privacy-preserving learning. It reports AI embedded across the software lifecycle for productivity and testing, and AI-driven real-time threat detection in security operations.

Impact 30%
69
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
99

Updated Oct 7, 2026 · TRV-2026-1307

74Index score

AI problems · 770

81
Media & ArtsStableModerate evidence · 1 source

Integration of AI into music creation enables new forms of infringement that complicate protection of musical works through illegal copying and digital remixing.

The peer-reviewed article analyzes how digital technologies have transformed protection of musical works, moving from analog media to online platforms. It identifies streaming piracy, illegal copying, AI use, and digital remixing as emerging threats and reviews legal and technical tools including registration, DRM, watermarks, and blockchain, alongside international and Russian practice.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
91

Updated Aug 27, 2026 · TRV-2026-0910

73Index score
82
HealthStableModerate evidence · 1 source

The model missed 21.2% of expert-defined high-risk cases with sensitivity of 78.8%, and three-level risk stratification accuracy was only 76.3% with 98.6% of errors being downward shifts that underestimate risk.

Researchers retrospectively tested ChatGPT on 300 histopathologically confirmed oral lichen planus cases with at least 24 months of follow-up, using serial clinical records, intraoral photographs, and histopathology reports. Compared with blinded expert panel consensus, the model achieved 94.7% accuracy for trajectory classification and 78.8% sensitivity with 99.6% specificity for high-risk detection as of the August 2026 publication.

Impact 30%
69
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
89

Updated Aug 16, 2026 · TRV-2026-0788

73Index score
83
HealthStableModerate evidence · 1 source

When tuned for ≥95% sensitivity screening, the models suffered a steep parallel decline in specificity and cannot safely eliminate the need for lumbar puncture, with top non-linear models showing severe training optimism.

Researchers retrospectively analyzed 306 infants aged 1 to 90 days hospitalized between 2014 and 2022 in Khorasan Razavi, Iran, using CSF culture via lumbar puncture as the gold standard, to train nine machine learning classifiers on routine non-invasive paraclinical markers with nested cross-validation and SHAP interpretation.

Impact 30%
69
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
89

Updated Aug 16, 2026 · TRV-2026-0783

73Index score
84
ClimateStableModerate evidence · 1 source

Fixed 20-epoch training without checkpoint selection wasted most compute, with 78% to 84% of total emissions occurring after the optimal checkpoint had already been reached.

In a study published August 12, 2026, researchers quantified CO2eq emissions for training ResNet-50, DenseNet-121 and EfficientNet-B0 on 128,907 chest radiographs for 20 epochs. They found validation loss minima at median epochs 2 to 4, meaning most emissions occurred after the best checkpoint, and compared retrospective selection, prospective early stopping, and fixed-epoch training on AUC and energy use.

Impact 30%
69
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
89

Updated Aug 14, 2026 · TRV-2026-0753

73Index score

Recomputed live from the record · Oct 11, 2026, 8:54 AM