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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
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AI gains · 932

105
HealthStableModerate evidence · 1 source

Integrating surface-enhanced Raman spectroscopy with a support vector machine model enabled rapid species-level identification of seven clinically common Nocardia spp. at 99.47% accuracy to guide clinical treatment.

On 2026-09-08, a peer-reviewed study reported an intelligent analytical model combining surface-enhanced Raman spectroscopy with machine learning to identify seven clinically common Nocardia species from cultured clinical isolates. Using 46 strains and 64 spectra per strain, the team compared nine models and found the support vector machine achieved 99.47% accuracy.

Impact 30%
69
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
94

Updated Sep 9, 2026 · TRV-2026-1029

74Index score
106
HealthStableModerate evidence · 1 source

YOLOv11 Nano achieved multiclass detection and Gartland I-III classification of pediatric supracondylar fractures with ~91-93% accuracy across validation strategies, improving further with bone segmentation.

Researchers developed a YOLOv11 Nano model to detect pediatric supracondylar fractures and classify Gartland subtypes I-III on 1082 elbow radiographs from 2004-2018, testing three patient-level validation schemes and adding bone segmentation and explainable AI visualizations. They also conducted a PRISMA-DTA meta-analysis of four studies totaling 2232 images comparing CNN and radiomics approaches.

Impact 30%
69
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
93

Updated Sep 7, 2026 · TRV-2026-1008

74Index score
107
EducationStableModerate evidence · 1 source

An 8-hour hands-on AI rotation delivered to 27 radiology residents over three years was completed by all participants with consistent structure, yielding approximate 80-90% post-training quiz performance and favorable ratings for overall value.

Between 2023 and 2025, educators at a single academic institution integrated an 8-hour interactive AI rotation into diagnostic radiology residency, combining didactics with lab modules on convolution, radiomics, machine learning, deep learning, evaluation, bias, and clinical cases for 27 residents across three cohorts.

Impact 30%
69
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
93

Updated Sep 7, 2026 · TRV-2026-1007

74Index score
108
HealthStableModerate evidence · 1 source

Mistral-NeMo verified orthopaedic lower-extremity billing by correctly identifying 90% of true CPT codes and rejecting 99.8% of incorrect codes when provided with billing descriptions.

A peer-reviewed study tested the Mistral-NeMo language model on 1000 operative notes from 177 providers to verify Current Procedural Terminology codes for lower-extremity orthopaedic surgery. When CPT billing descriptions were included in the prompt, the model correctly identified 90% of true codes and rejected 99.80% of incorrect codes.

Impact 30%
69
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
93

Updated Sep 7, 2026 · TRV-2026-1003

74Index score

AI problems · 770

105
LaborStableModerate evidence · 1 source

Low-skilled workers are subjected to stronger technological control, and large language models disproportionately influence women, younger demographics, professional skilled laborers, and higher-income groups in the tertiary industry.

A peer-reviewed study published November 17, 2025 analyzed skill heterogeneity as technology moves from physical automation to cognitive automation. It assessed both substitution and control, finding limited substitution for high- and low-skilled workers, but stronger control for low-skilled workers, and compared sectoral effects of automation versus large language models.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
84

Updated Jul 20, 2026 · TRV-2026-0451

72Index score
106
LaborStableModerate evidence · 1 source

Industrial AI deployment creates ongoing ethical threats linked to entrusting machines with autonomy and decision-making responsibility.

Published December 2025 in Production Engineering Archives, this peer-reviewed theoretical paper reviews how artificial intelligence is being used in industry, including cobots, algorithmic management, employee monitoring, sustainability efforts, and generative AI, and summarizes existing international legal frameworks for safe and ethical AI.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
84

Updated Jul 20, 2026 · TRV-2026-0411

72Index score
107
Media & ArtsStableModerate evidence · 1 source

Generative AI may amplify existing dysfunctions of streaming platforms, threaten livelihoods of music professionals, and raise governance and transparency concerns.

Published December 5, 2025, this peer-reviewed study investigated how AI and Generative AI affect music streaming. Using two focus groups with users and with artists/performers, it explored perceptions of AI-generated music for listening and for artists' position and opportunities within the streaming model.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
84

Updated Jul 20, 2026 · TRV-2026-0410

72Index score
108
LaborStableModerate evidence · 1 source

Human contributions were invisibilised in AI-foregrounded products, with potential displacement in ideation and persistent deskilling and precarious flexible employment for small creative firms.

Published October 28 2024, this peer-reviewed study examined 6 commercial products using AI in creative industries to assess labor market effects. It found AI products were more labor intensive than traditional media because they required both traditional production skills and new computational expertise, while also enabling broader exploration in the ideation phase.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
84

Updated Jul 20, 2026 · TRV-2026-0350

72Index score

Recomputed live from the record · Oct 11, 2026, 12:02 PM