Truace
Subscribe
The Index recomputed live from the record

What the evidence says.What the public feels.

The record holds 939 sourced gains and 772 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.

939 gains
772 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.

1,711 results
Show filters and sorting

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

AI gains · 939

561
HealthStableModerate evidence · 1 source

An ensemble Stacking model using baseline clinical, neurological, and MRI features predicted one-year AIS grade and motor/independence scores in TCSCI patients with high discrimination and low error on external testing.

By August 2026, researchers had developed and externally validated a two-layer Stacking ensemble that integrates baseline clinical data, neurological assessments, and cervical MRI features to predict one-year outcomes after traumatic cervical spinal cord injury. In 340 patients analyzed, the model predicted AIS grade with AUC 0.85 and predicted continuous motor and independence scores with R8 above 0.986.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
86

Updated Aug 4, 2026 · TRV-2026-0639

67Index score
562
HealthStableModerate evidence · 1 source

Deep learning models demonstrated proof-of-concept ability to predict knee osteoarthritis progression from medical imaging, with internal median AUCs up to 0.87 for surgical endpoints.

This PRISMA systematic review evaluated 33 peer-reviewed studies (2019-2026) comprising 50 deep learning models that predict knee osteoarthritis progression from medical imaging. It extracted AUC as primary outcome, categorized nine different progression definitions, and assessed bias with PROBAST-AI, finding median internal AUCs of 0.87 for surgery, 0.78 for structural, and 0.79 for symptomatic endpoints.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
86

Updated Aug 4, 2026 · TRV-2026-0638

67Index score
563
ClimateStableModerate evidence · 1 source

Hybrid STICS plus random forest integration improved accuracy and interpretability of apple fruit maturity date prediction to support harvest timing and climate adaptation across China's apple regions.

Researchers developed a hybrid framework that couples the STICS biophysical crop model with machine learning to predict apple fruit maturity dates across China. Using phenology records from 24 sites and weather data from 250 stations for 1991-2020, they found a random forest integration improved prediction accuracy and interpretability at regional scales.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
86

Updated Aug 3, 2026 · TRV-2026-0632

67Index score
564
HealthStableModerate evidence · 1 source

An exploratory Light Gradient Boosting Machine model predicted 1-week willingness to reuse rubber dam isolation after microscopic root canal treatment with AUC 0.939 in held-out test and 0.983 in temporal validation.

Researchers retrospectively analyzed 306 patients who had microscopic root canal treatment with rubber dam isolation between May and November 2025, defining willingness to reuse at 1-week follow-up as the outcome, with 246 willing and 60 unwilling. They trained six models on 26 variables and found the LightGBM model retained 12 predictors and achieved the highest exploratory AUCs of 0.939 and 0.983.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
86

Updated Aug 3, 2026 · TRV-2026-0631

67Index score

AI problems · 772

561
HealthStableModerate evidence · 1 source

He didn’t reveal the attack then, but he sounded a warning about the march of AI: “the risk is that AI develops in a way in which humans are no longer in control of what AI is producing.” But Albanese noted, too, that two countries, the US and China, would dominate the world’s response to the new technology.

When the Australian prime minister, Anthony Albanese, sat down for an interview in the heart of Silicon Valley at the weekend he had known for two days that his was the first government known to have been attacked by a rogue AI agent. He didn’t reveal the attack then, but he sounded a warning about the march of AI: “the risk is that AI develops in a way in which humans are no longer in control of what AI is producing.” But Albanese noted, too, that two countries, the US and China, would dominate the world’s response to the new technology.

Impact 30%
49
Evidence 25%
62
Scale 20%
85
Confidence 15%
62
Recency 10%
97

Updated Sep 26, 2026 · TRV-2026-1182

66Index score
562
PolicyStableModerate evidence · 1 source

Davey is expected to call for a new global movement to work together to protect humanity from the risks of super-intelligent AI, saying that the IAEA was built by nations “working together to control a technology that could destroy us all”, but warning that the future of AI is being decided by “a tiny number of the richest and most powerful in California and in Beijing” with no guardrails to slow down development.

Ed Davey is to call for a global nuclear-style non-proliferation treaty to halt the development of super-intelligent AI when he makes his keynote speech at the Liberal Democrat conference, accusing Andy Burnham of relying on Donald Trump and “tech bros” to solve the problem. When he addresses the faithful on the final day of the gathering in Brighton, the party leader will call for a global pause on super-intelligent AI, comparing it to a nuclear arms race that could result in technology that could “destroy us all”.

Impact 30%
49
Evidence 25%
62
Scale 20%
85
Confidence 15%
62
Recency 10%
96

Updated Sep 22, 2026 · TRV-2026-1160

66Index score
563
BusinessStableModerate evidence · 1 source

Tesla's deployment of wheel-free Cybercabs on Austin streets triggered an immediate federal safety probe.

On September 4, 2026, TechStartups reported a cluster of AI developments: OpenAI released GPT-6 Astra and declared the AGI era, Tesla put wheel-free Cybercabs on Austin streets and drew a federal safety probe, Crusoe reached a $30 billion valuation, and Congress moved to inventory rogue AI agents.

Impact 30%
49
Evidence 25%
62
Scale 20%
85
Confidence 15%
62
Recency 10%
93

Updated Sep 9, 2026 · TRV-2026-1021

66Index score
564
PolicyStableModerate evidence · 1 source

Frontier AI models with growing autonomy and threat capabilities could materially alter cyber-risk and destabilize the highly interconnected global financial system.

On 31 August 2026, Bank of England governor Andrew Bailey, writing as chair of the Financial Stability Board, warned G20 finance ministers and central bank governors that frontier AI models are showing sophisticated autonomy and threat capabilities that could destabilize the global financial system through cyber-disruption spreading across jurisdictions.

Impact 30%
49
Evidence 25%
62
Scale 20%
85
Confidence 15%
62
Recency 10%
92

Updated Aug 31, 2026 · TRV-2026-0929

66Index score

Recomputed live from the record · Oct 13, 2026, 8:42 PM