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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
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AI gains · 939

437
HealthStableModerate evidence · 1 source

AI-assisted ultrasound of the rectus femoris quantified intramuscular fat percentage (FATi), which was independently associated with diabetic nephropathy and adverse metabolic profiles in patients with diabetes.

In a cross-sectional study of 120 diabetes outpatients at a tertiary Endocrinology and Nutrition Department, researchers used the PIIXMED AI-system to analyze rectus femoris ultrasound images and quantify intramuscular fat percentage (FATi). By publication date 2026-08-24, they reported that higher FATi was associated with adverse metabolic profiles and microvascular complications.

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

Updated Aug 26, 2026 · TRV-2026-0900

68Index score
438
HealthStableModerate evidence · 1 source

Stacked ensembles combining five CNN backbones improved automated detection and size stratification of periapical lesions on cropped intraoral radiographs, reaching high accuracy and high sensitivity for very small lesions on internal testing.

Researchers built stacked deep learning ensembles to detect periapical lesions and stratify them by radiographic size on intraoral radiographs. Using 146 cropped and augmented images, five CNN backbones were combined with MLR and XGBoost meta-learners and evaluated on an internal hold-out test set.

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

Updated Aug 26, 2026 · TRV-2026-0899

68Index score
439
HealthStableModerate evidence · 1 source

Adapted iPsRS model using 13 individual-level SDoH predictors predicted 1-year all-cause hospitalization in a general adult cohort with AUROC up to 0.671, enabling equity-aware risk stratification for clinical care.

Researchers adapted the individualized polysocial risk score, originally built for type 2 diabetes, to a disease-agnostic cohort of 17,857 adults at University of Florida Health. Using 13 individual-level social determinants of health, they trained XGBoost and logistic regression models to predict all-cause hospitalization within one year, testing multiple fine-tuning levels and sampling strategies.

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

Updated Aug 26, 2026 · TRV-2026-0897

68Index score
440
HealthStableModerate evidence · 1 source

Machine learning analysis of breath volatiles identified candidate markers that discriminated culture-confirmed melioidosis from other febrile illnesses with perfect AUC in a small test set and tracked culture status and treatment time during antibiotics.

By the publication date of 2026-08-25, a pilot study had collected breath samples from 17 melioidosis patients and 8 febrile controls and used two-dimensional gas chromatography mass spectrometry combined with machine learning feature selection to identify volatile signatures of infection and treatment course.

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

Updated Aug 26, 2026 · TRV-2026-0896

68Index score

AI problems · 772

437
EducationStableModerate evidence · 1 source

Generative AI chatbots in higher education raise concerns around academic integrity, labour displacement, and embedded biases that require a critical approach.

The peer-reviewed commentary from April 2024 analyzes the rapid uptake of generative AI chatbots like ChatGPT in universities, noting both potential to enhance teaching, research, administration and student support and simultaneous pressures from hype and commercial edtech actors.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
84

Updated Jul 20, 2026 · TRV-2026-0438

67Index score
438
BusinessStableModerate evidence · 1 source

Existing HRM frameworks fall short of capturing the novel attributes, complexities and impacts of generative AI on workforce dynamics and organizational operations, introducing unique challenges for human resources.

On 2024-04-11 this peer-reviewed paper proposed a strategic human resource management framework for integrating generative artificial intelligence in business, arguing existing HRM frameworks fall short and outlining components including alignment with business objectives, seizing opportunities, resource assessment and orchestration, re-institutionalization and continuous learning.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
84

Updated Jul 20, 2026 · TRV-2026-0437

67Index score
439
HealthStableModerate evidence · 1 source

Poorly performing predictive AI models are misleading and may lead to wrong clinical decisions that can be detrimental to patients and increase financial costs, with classification measures being improper at clinically relevant thresholds.

Published in December 2025, this Viewpoint in The Lancet Digital Health evaluates how to validate predictive AI models that estimate binary outcome probabilities for clinical use. The authors reviewed 32 performance measures across five domains and examined whether each measure is proper and whether it accounts for misclassification costs, illustrating findings with the ADNEX model for ovarian tumour malignancy.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
84

Updated Jul 20, 2026 · TRV-2026-0434

67Index score
440
LaborStableModerate evidence · 1 source

Gen-AI in creative media and arts industries raises concerns that human creative labour could disappear.

Published May 22, 2024, this peer-reviewed article analyzes generative AI's transformative role in creative media and arts industries through the lens of the 2023 Writers' and Actors' strikes. It critiques the prevailing 'replacing tasks' narrative and applies a meaningful work framework to argue for coexistence that amplifies rather than supplements human creativity, using Jurassic Park's VFX transition as a historical parallel.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
84

Updated Jul 20, 2026 · TRV-2026-0432

67Index score

Recomputed live from the record · Oct 13, 2026, 7:57 AM