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The Index recomputed live from the record

What the evidence says.What the public feels.

The record holds 934 sourced gains and 771 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.

934 gains
771 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.

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AI gains · 934

289
HealthNewly addedModerate evidence · 1 source

Final-year nursing students receiving AI-adaptive simulation integrated with a workforce decision-support system showed greater gains in simulated leadership performance, team performance, and self-efficacy at Week 10 compared to controls.

In a randomized controlled trial of 130 final-year nursing students, researchers compared traditional simulation to AI-adaptive simulation integrated with an AI-based workforce decision-support system. By Week 10, the AI group showed significantly larger improvements in leadership performance on the Creighton Simulation Evaluation Instrument, plus gains in team performance and self-efficacy.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
98

Updated Oct 3, 2026 · TRV-2026-1262

68Index score
290
HealthNewly addedModerate evidence · 1 source

Fine-tuned LLaMA models extracted symptom presence and severity from free-text notes with high F1 scores, enabling the first structured quarterly trajectories for VNS patients.

Researchers built a two-stage large language model pipeline to turn free-text clinical notes into structured symptom severity data for vagus nerve stimulation patients, part of NIH-funded work U54AT012307. Using 1427 annotated notes from 95 patients, LLaMA models classified symptoms and then graded severity, producing quarterly trajectories for 23 VNS patients compared to a 10-patient NSQIP surgical control.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
98

Updated Oct 3, 2026 · TRV-2026-1260

68Index score
291
HealthNewly addedModerate evidence · 1 source

AI-based algorithms improve detection of scaphoid fractures including occult fractures on plain radiographs to support treatment decisions, while navigation and robotics improve screw accuracy and reduce radiation and guidewire attempts.

This peer-reviewed review from October 2026 synthesizes digital orthopedic techniques for scaphoid fractures, including AI-based radiograph interpretation, finite element analysis, virtual surgical planning, navigation, robotics, and 3D printing for guides and custom prostheses.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
98

Updated Oct 3, 2026 · TRV-2026-1259

68Index score
292
ScienceNewly addedModerate evidence · 1 source

Random Forest predicted atmospheric attenuation for free-space optical links more accurately than deep learning models on a 1500-sample synthetic Iraqi weather dataset, with dust concentration and visibility as top drivers and faster training and inference.

A study evaluated 15 machine learning, deep learning and hybrid models for predicting atmospheric attenuation in free-space optical communications under five Iraqi weather regimes. Using a 1500-sample synthetic dataset derived from physical propagation models, Random Forest achieved R2 0.9654 and RMSE 1.324 dB/km, outperforming the best deep learning model at R2 0.7766 and slightly edging the best hybrid at 0.9571.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
98

Updated Oct 3, 2026 · TRV-2026-1258

68Index score

AI problems · 771

289
Media & ArtsStableModerate evidence · 1 source

LLM-generated creative writing shows higher stylistic uniformity and tight clustering by model, lacking the broader heterogeneity and individual diversity seen in human-authored stories.

Researchers compared human-authored short stories with stories generated by GPT-3.5, GPT-4, and Llama 70b in response to the same prompts, using Burrows' Delta and clustering methods including hierarchical clustering and multidimensional scaling to visualize stylistic relationships.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
91

Updated Aug 25, 2026 · TRV-2026-0883

68Index score
290
Media & ArtsStableModerate evidence · 1 source

Users of AI art platforms showed limited awareness of structural issues, as cultural bias in training data and algorithmic transparency were rated lower in importance than autonomy and usability.

A mixed-methods study examined Midjourney, Runway ML and Stable Diffusion to understand how generative AI reshapes artistic subjectivity. Twelve practitioners were interviewed in spring 2025 to build a grounded-theory framework, followed by a survey of 426 users in summer 2025 evaluated with CRITIC weighting.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
91

Updated Aug 25, 2026 · TRV-2026-0882

68Index score
291
ScienceStableModerate evidence · 1 source

The same AI analysis consistently produced two themes based on subtle misrepresentations that could have misled evaluation results without human auditing.

In a quality improvement program evaluation, researchers used artificial intelligence to identify themes in interview data. By the publication date of 2026-08-24, the approach had produced four replicable themes grounded in the data, while also generating two consistently identified themes that were subtle misrepresentations.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
91

Updated Aug 25, 2026 · TRV-2026-0881

68Index score
292
HealthStableModerate evidence · 1 source

Existing practical approaches for implementing and evaluating transparency across the full lifecycle of AI-enabled medical devices are fragmented and lack systematic structure.

Published August 2026, this peer-reviewed synthesis addresses transparency as a foundational condition for trustworthy AI in healthcare. It finds current methods to operationalize transparency across AI-enabled medical devices are fragmented, and proposes a SaMD lifecycle framework to map regulatory and standards requirements to concrete development and governance steps.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
91

Updated Aug 25, 2026 · TRV-2026-0879

68Index score

Recomputed live from the record · Oct 12, 2026, 1:30 PM