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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

541
HealthStableModerate evidence · 1 source

Among 358 medical students surveyed, higher digital literacy was associated with more positive attitudes towards artificial intelligence and was the strongest independent factor in adjusted analysis.

A peer-reviewed cross-sectional study of 358 medical students from November 2025 to January 2026 examined factors linked to attitudes toward AI using online questionnaires including digital literacy and emotional intelligence scales. Most students had used AI, but majorities reported ethical or legal concerns and worries about reduced clinical reasoning.

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

Updated Aug 6, 2026 · TRV-2026-0667

67Index score
542
HealthStableModerate evidence · 1 source

TrialTriage achieved perfect concordance with ground truth on 90 synthetic phase I oncology cases and reclassified ambiguous cases to definitive eligibility after capturing investigator email replies, processing cases in seconds compared to slower manual review.

Researchers developed TrialTriage, a semiautonomous prescreening workflow on the n8n platform that uses large language model extraction from clinical narratives and investigator email replies plus a 7-criterion deterministic rule engine to classify phase I oncology trial eligibility, automatically emailing investigators when information is missing and reclassifying after reply capture.

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

Updated Aug 6, 2026 · TRV-2026-0666

67Index score
543
HealthStableModerate evidence · 1 source

An ensemble of five machine learning algorithms applied to spinal anesthesia cases identified actionable risk factors for postoperative nausea and vomiting, with postoperative fentanyl as the strongest contributor, and was described as accurate enough to support PONV prediction.

A retrospective study at Tohoku University Hospital applied an ensemble of five machine learning algorithms to 4,574 spinal anesthesia cases from 2010 to 2022, using propensity score matching to compare 269 patients with PONV to 269 without, to predict and explain postoperative nausea and vomiting within 24 hours.

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

Updated Aug 6, 2026 · TRV-2026-0665

67Index score
544
HealthStableModerate evidence · 1 source

A Bayesian joint modeling system that integrates longitudinal CD4+ counts and CD4/CD8 ratios predicted 5- to 7-year risk of incomplete immune reconstitution in people living with HIV with high discrimination, enabling real-time identification of high-risk patients for timely intervention.

Researchers developed a dynamic joint prediction system for incomplete immune reconstitution risk in people living with HIV using Bayesian joint modeling of longitudinal CD4+ counts and CD4/CD8 ratios from 21,862 patients across 31 Chinese provinces between 2003 and 2024.

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

Updated Aug 6, 2026 · TRV-2026-0664

67Index score

AI problems · 772

541
EducationStableModerate evidence · 1 source

In India, creators and users face unresolved copyright risk because the 1957 Act does not define ownership of AI-generated works or the legality of training on copyrighted data.

By June 2026, generative models such as GPT-4, Stable Diffusion and Mid journey were described as capable of producing entire works independently, while India's Copyright Act of 1957 remained drafted for human creators and relatively silent on such output.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
82

Updated Jul 13, 2026 · TRV-2026-0144

67Index score
542
SportsStableModerate evidence · 1 source

Current AI studies for sport-related concussion are frequently constrained by small or imbalanced samples, inconsistent definitions, limited external validation, and poor model interpretability.

By December 2025, a scoping review of six databases identified 55 studies of artificial intelligence across the concussion care pathway, from detection and diagnosis using EEG, speech and motor data to monitoring with wearables, mouthguards and video, plus prognosis and prevention modeling.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
82

Updated Jul 13, 2026 · TRV-2026-0141

67Index score
543
CrimeStableModerate evidence · 1 source

AI systems exhibit a persistent black box problem that blocks trust and adoption in high-stakes domains including healthcare, finance, and criminal justice, while dark AI uses like deepfakes and AI-powered cyberattacks create governance risks.

By July 2026, this systematic review synthesized 141 studies to map seven emerging paradigms beyond generative AI, including Emotional and Empathetic AI, Social AI, Agentic AI, Multimodal AI, Explainable AI, and Responsible AI, documenting a shift from purely technical research to socio-technical integration.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
82

Updated Jul 13, 2026 · TRV-2026-0133

67Index score
544
PolicyStableModerate evidence · 1 source

Generative deepfake systems produce reputational, identity-based and corporate harms through chains of developers, prompting users, platforms and distributors that ordinary Saudi and Jordanian tort doctrine struggles to remedy.

As of its July 2, 2026 publication, this peer-reviewed article analyzes how deepfake and synthetic-media harms are produced through combined conduct of generative-model developers, prompting users, platforms and secondary distributors, and argues ordinary tort doctrine does not easily resolve the resulting civil-liability problem in Saudi and Jordanian law.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
82

Updated Jul 13, 2026 · TRV-2026-0132

67Index score

Recomputed live from the record · Oct 13, 2026, 7:02 PM