Objective: Electronic health records (EHR) data are prone to missingness and errors. Previously, we devised an "enriched" chart review protocol where a "roadmap" of auxiliary diagnoses (anchors) was used to recover missing values in EHR data (e.g., a diagnosis of impaired glycemic control might imply that a missing hemoglobin A1c value would be considered unhealthy). Still, chart reviews are expensive and time-intensive, which limits the number of patients whose data can be reviewed. Now, we investigate the accuracy and scalability of a roadmap-driven algorithm, based on ICD-10 codes (International Classification of Diseases, 10th revision), to mimic expert chart reviews and recover missing values. Materials and Methods: In addition to the clinicians' original roadmap from our previous work, we consider new versions that were iteratively refined using large language models (LLM) in conjunction with clinical expertise to expand the list of auxiliary diagnoses. Using chart reviews for 100 patients from the EHR at an extensive learning health system, we examine algorithm performance with different roadmaps. Using the larger study of $1000$ patients, we applied the final algorithm, which used a roadmap with clinician-approved additions from the LLM. Results: The algorithm recovered as much, if not more, missing data as the expert chart reviewers, depending on the roadmap. Discussion: Clinically-driven algorithms (enhanced by LLM) can recover missing EHR data with similar accuracy to chart reviews and can feasibly be applied to large samples. Extending them to monitor other dimensions of data quality (e.g., plausability) is a promising future direction.

Vision-language models trained on large-scale multimodal datasets show strong demographic biases, but the role of training data in producing these biases remains unclear. A major barrier has been the lack of demographic annotations in web-scale datasets such as LAION-400M. We address this gap by creating person-centric annotations for the full dataset, including over 276 million bounding boxes, perceived gender and race/ethnicity labels, and automatically generated captions. These annotations are produced through validated automatic labeling pipelines combining object detection, multimodal captioning, and finetuned classifiers. Using them, we uncover demographic imbalances and harmful associations, such as the disproportionate linking of men and individuals perceived as Black or Middle Eastern with crime-related and negative content. We also show that 60-70% of gender bias in CLIP and Stable Diffusion can be linearly explained by direct co-occurrences in the data. Our resources establish the first large-scale empirical link between dataset composition and downstream model bias.

As military organisations consider integrating large language models (LLMs) into command and control (C2) systems for planning and decision support, understanding their behavioural tendencies is critical. This study develops a benchmarking framework for evaluating aspects of legal and moral risk in targeting behaviour by comparing LLMs acting as agents in multi-turn simulated conflict. We introduce four metrics grounded in International Humanitarian Law (IHL) and military doctrine: Civilian Target Rate (CTR) and Dual-use Target Rate (DTR) assess compliance with legal targeting principles, while Mean and Max Simulated Non-combatant Casualty Value (SNCV) quantify tolerance for civilian harm. We evaluate three frontier models, GPT-4o, Gemini-2.5, and LLaMA-3.1, through 90 multi-agent, multi-turn crisis simulations across three geographic regions. Our findings reveal that off-the-shelf LLMs exhibit concerning and unpredictable targeting behaviour in simulated conflict environments. All models violated the IHL principle of distinction by targeting civilian objects, with breach rates ranging from 16.7% to 66.7%. Harm tolerance escalated through crisis simulations with MeanSNCV increasing from 16.5 in early turns to 27.7 in late turns. Significant inter-model variation emerged: LLaMA-3.1 selected an average of 3.47 civilian strikes per simulation with MeanSNCV of 28.4, while Gemini-2.5 selected 0.90 civilian strikes with MeanSNCV of 17.6. These differences indicate that model selection for deployment constitutes a choice about acceptable legal and moral risk profiles in military operations. This work seeks to provide a proof-of-concept of potential behavioural risks that could emerge from the use of LLMs in Decision Support Systems (AI DSS) as well as a reproducible benchmarking framework with interpretable metrics for standardising pre-deployment testing.

Evaluating machine translation (MT) quality for under-resourced African languages remains a significant challenge, as existing metrics often suffer from limited language coverage and poor performance in low-resource settings. While recent efforts, such as AfriCOMET, have addressed some of the issues, they are still constrained by small evaluation sets, a lack of publicly available training data tailored to African languages, and inconsistent performance in extremely low-resource scenarios. In this work, we introduce SSA-MTE, a large-scale human-annotated MT evaluation (MTE) dataset covering 14 African language pairs from the News domain, with over 73,000 sentence-level annotations from a diverse set of MT systems. Based on this data, we develop SSA-COMET and SSA-COMET-QE, improved reference-based and reference-free evaluation metrics. We also benchmark prompting-based approaches using state-of-the-art LLMs like GPT-4o, Claude-3.7 and Gemini 2.5 Pro. Our experimental results show that SSA-COMET models significantly outperform AfriCOMET and are competitive with the strongest LLM Gemini 2.5 Pro evaluated in our study, particularly on low-resource languages such as Twi, Luo, and Yoruba. All resources are released under open licenses to support future research.

AMD's shares surge on deal to supply AI chips to OpenAI United States chipmaker AMD will supply artificial intelligence chips to OpenAI in a multi-year deal that would bring in tens of billions of dollars in annual revenue and give the ChatGPT creator the option to buy up to roughly 10 percent of the company. Shares of the chipmaker surged more than 34 percent on Monday when the deal was announced, putting them on track for their biggest one-day gain in more than nine years and adding roughly $80bn to the company's market value. "We view this deal as certainly transformative, not just for AMD, but for the dynamics of the industry," AMD executive vice president Forrest Norrod told the Reuters news agency. The agreement closely ties the startup at the centre of the AI boom to AMD, one of the strongest rivals of Nvidia, which recently agreed to make substantial investments in OpenAI. Analysts said it was a significant vote of confidence in AMD's AI chips and software but is unlikely to dent Nvidia's dominance, as the market leader continues to sell every AI chip it can make.

New Supreme Court term will reshape Trump's powers The US Supreme Court begins its new term on Monday with a docket already full of potentially significant cases that could define the scope of Donald Trump's presidential authority - and the prospect of more to come. In the eight months that Trump has been back in the White House, he has tested the limits of executive power, unilaterally implementing new policies, slashing federal budgets and workforce, and attempting to bring previously independent agencies and institutions more directly under his control. The latest brewing legal battle comes from the president's attempts to take control of state National Guard units and deploy them in cities where he claims there is public unrest and rampant crime - over the objection of local and state officials. In Oregon, a federal judge has issued orders blocking Trump's deployment of troops to Portland. An appeals court is set to review the move in the coming days.

The tiny shark and a ghost-like crab are two of the latest species uncovered in a yearslong expedition. Breakthroughs, discoveries, and DIY tips sent every weekday. Oceanographers scouring the waters off of Western Australia have discovered two new deep-sea oddities . On October 6, Australia's Commonwealth Scientific and Industrial Research Organization (CSIRO) showcased these new species originally collected in 2022: a bioluminescent lanternshark and a tiny, semi-translucent porcelain crab . The team revealed two of its initial finds--the painted hornshark and the ridged-egg catshark --in 2023.

The Karnak Temple's age has stumped archaeologists for decades. Breakthroughs, discoveries, and DIY tips sent every weekday. The expansive ruins of Karnak Temple provide an unprecedented window into ancient Egypt . After decades of archaeological excavation work, researchers have amassed a treasure trove of information about the kingdom's history, politics, culture, and religious practices. But experts have long remained divided on one major detail: Karnak's actual age.

British microcomputers were among more than 100,000 foreign-made parts contained in Russian missiles and drones used in Sunday's deadly strikes on Ukraine, Volodymyr Zelensky has said. The Ukrainian president called for further effective sanctions after saying parts originating in allied countries including Germany, Japan and the US have been identified in Russian weapons. The Department for Business and Trade (DBT) said it had recently undertaken efforts to crack down on UK firms whose products have continued to make their way into Russia's military supply chain. We take reports of goods from UK companies being found in Russian weaponry incredibly seriously, a government spokesperson said. The spokesperson said the government had banned the export of thousands of goods to Russia including every battlefield item Ukraine has brought to our attention, adding that they have imposed the most the most severe package of sanctions. What are the sanctions on Russia and are they working?

America's richest real estate tycoon disowns son with shockingly icy 12-word statement after'man cave' plans went terribly wrong Horrific stab wounds suffered by grease truck driver, 69, 'stabbed by Mark Sanchez' with NFL star facing up to six years in prison Taylor Swift makes surprise confession on her song'about ex Joe Alwyn' as she insists fans have'always had the wrong idea' about it Sinister notes that are plaguing remote county explodes as fears mount over creepy messages: 'What else could they do?' Key North Atlantic current is on the brink of COLLAPSING - plunging Europe into a'Little Ice Age', scientists warn Visionary billionaire died in a suspicious house fire. Then a mysterious will emerged... CBS staff in panic as anti-woke firebrand Bari Weiss takes control with no-nonsense show on America's most divisive issues Trump's war room plots savage bloodbath as countdown enters final hours: Live updates Trump sends Navy officers wild with powerful message to liberals claiming he's'unwell' We got hopelessly hooked on a trendy'wellness' tonic. We thought it was harmless but our descent into addiction left us depressed, in debt... and in rehab Judge speaks out after her $1.5m mansion'exploded' in suspected arson attack after she defied Trump order Mark Sanchez's alleged victim's family breaks silence as grim photos emerge after violent attack So many women suffer bloated, uncomfortable guts, says DR EMILY LEEMING. Here's the 7 simple cures I give my patients - you won't have read these before My son made a horrifying accusation about me in therapy... it's destroyed our relationship: DEAR JANE Ex-NFL star Mark Sanchez'thought he'd been shot and pounded on window of pub to get help', bartender reveals Nicole Kidman's friends tear into Keith Urban over bombshell split: 'Total 180 on who he is' Real Housewives of Atlanta vet Porsha Williams reveals she is dating a woman... after ex Simon was deported by ICE US billionaire retail estate tycoon is ordered to sell off his'exceptional' £36million London mansion in bitter divorce battle with ex-wife My husband works in Dubai and has cheated on me at least three times so far.