Social signals predict contemporary art prices better than visual features, particularly in emerging markets.

What determines the price of an artwork? This article leverages a comprehensive and novel dataset on art auctions of contemporary artists to examine the impact of social and visual features on the valuation of artworks across global markets. Our findings indicate that social signals allow us to predict the price of artwork exceptionally well, even approaching the professionals' prediction accuracy, while the visual features play a marginal role. This pattern is especially pronounced in emerging markets, supporting the idea that social signals become more critical when it is more difficult to assess the quality. These results strongly support that the value of artwork is largely shaped by social factors, particularly in emerging markets where a stronger preference for "buying an artist" than "buying an artwork." Additionally, our study shows that it is possible to boost experts' performance, highlighting the potential benefits of human-machine models in uncertain or rapidly changing markets, where expert knowledge is limited.

Artificial intelligence- and computer-assisted navigation for shoulder surgery.

Background: Over the last few decades, shoulder surgery has undergone rapid advancements, with ongoing exploration and the development of innovative technological approaches. In the coming years, technologies such as robot-assisted surgeries, virtual reality, artificial intelligence, patient-specific instrumentation, and different innovative perioperative and preoperative planning tools will continue to fuel a revolution in the medical field, thereby pushing it toward new frontiers and unprecedented advancements. In relation to this, shoulder surgery will experience significant breakthroughs. Main body: Recent advancements and technological innovations in the field were comprehensively analyzed. We aimed to provide a detailed overview of the current landscape, emphasizing the roles of technologies. Computer-assisted surgery utilizing robotic- or image-guided technologies is widely adopted in various orthopedic specialties. The most advanced components of computer-assisted surgery are navigation and robotic systems, with functions and applications that are continuously expanding. Surgical navigation requires a visual system that presents real-time positional data on surgical instruments or implants in relation to the target bone, displayed on a computer monitor. There are three primary categories of surgical planning that utilize navigation systems. The initial category involves volumetric images, such as ultrasound echogram, computed tomography, and magnetic resonance images. The second type is based on intraoperative fluoroscopic images, and the third type incorporates kinetic information about joints or morphometric data about the target bones acquired intraoperatively. Conclusion: The rapid integration of artificial intelligence and deep learning into the medical domain has a significant and transformative influence. Numerous studies utilizing deep learning-based diagnostics in orthopedics have remarkable achievements and performance.

Transformation of social relationships in COVID-19 America: Remote communication may amplify political echo chambers.

The COVID-19 pandemic, with millions of Americans compelled to stay home and work remotely, presented an opportunity to explore the dynamics of social relationships in a predominantly remote world. Using the 1972-2022 General Social Surveys, we found that the pandemic significantly disrupted the patterns of social gatherings with family, friends, and neighbors but only momentarily. Drawing from the nationwide ego-network surveys of 41,033 Americans from 2020 to 2022, we found that the size and composition of core networks remained stable, although political homophily increased among nonkin relationships compared to previous surveys between 1985 and 2016. Critically, heightened remote communication during the initial phase of the pandemic was associated with increased interaction with the same partisans, although political homophily decreased during the later phase of the pandemic when in-person contacts increased. These results underscore the crucial role of social institutions and social gatherings in promoting spontaneous encounters with diverse political backgrounds.

Perception, performance, and detectability of conversational artificial intelligence across 32 university courses.

The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may utilize it to help with their school work-a possibility that has sparked ample discussion on the integrity of student evaluation processes in the age of artificial intelligence (AI). To date, it is unclear how such tools perform compared to students on university-level courses across various disciplines. Further, students' perspectives regarding the use of such tools in school work, and educators' perspectives on treating their use as plagiarism, remain unknown. Here, we compare the performance of the state-of-the-art tool, ChatGPT, against that of students on 32 university-level courses. We also assess the degree to which its use can be detected by two classifiers designed specifically for this purpose. Additionally, we conduct a global survey across five countries, as well as a more in-depth survey at the authors' institution, to discern students' and educators' perceptions of ChatGPT's use in school work. We find that ChatGPT's performance is comparable, if not superior, to that of students in a multitude of courses. Moreover, current AI-text classifiers cannot reliably detect ChatGPT's use in school work, due to both their propensity to classify human-written answers as AI-generated, as well as the relative ease with which AI-generated text can be edited to evade detection. Finally, there seems to be an emerging consensus among students to use the tool, and among educators to treat its use as plagiarism. Our findings offer insights that could guide policy discussions addressing the integration of artificial intelligence into educational frameworks.

Surgical outcome of locked facet in distractive flexion injury of the subaxial cervical spine: Single institution retrospective study.

The optimal surgical treatment for patients suffering from distractive flexion injury of the subaxial cervical spine with a locked facet (LF) is unknown. Closed reduction via an anterior or posterior approach is a treatment option for LF. We examined the surgical outcomes of patients treated for locked facet distractive flexion injury (LF-DFI) in this case series, with a particular emphasis on the surgical approach and reduction maneuver. We retrospectively analyzed the patients with distractive flexion injury of the subaxial cervical spine who underwent surgery at our hospital between November 2006 and April 2021. Patients who did not have facet subluxation or dislocation or those who achieved LF reduction prior to skin incision were excluded from this study. The patients were divided into 2 groups based on their initial approach, anterior or posterior approach. Perioperative clinical outcomes, including the American Spinal Cord Injury Association scale score, radiological changes, and complications were analyzed. This study enrolled 12 patients with LF-DFI. Four and 8 patients underwent the anterior and posterior approaches, respectively. The LF was reduced using an anterior approach with traction between the vertebral bodies in the anterior approach group and using a posterior approach with partial facetectomy in the posterior approach group. The preoperative American Spinal Cord Injury Association scale scores were as follows: A, 1 patient; B, 1 patient; C, 3 patients; D, 4 patients; and E, 3 patients. Nine patients showed no neurologic deterioration after surgery, whereas 2 had an aggravated neurologic status. Postoperatively, patients who underwent posterior open reduction did not exhibit worsened neurologic symptoms, whereas 2 patients who underwent the anterior approach showed worsened neurologic symptoms. At the final follow-up, all patients achieved radiological fusion, and no complications other than neurologic deterioration were identified. In terms of worsening postoperative neurologic status, a posterior approach using partial facetectomy for LF reduction is considered a safer surgical technique than an anterior approach. To avoid iatrogenic intraoperative cord injury, we recommend posterior approach in patients with LF-DFI.

Building an annotated corpus for automatic metadata extraction from multilingual journal article references.

Bibliographic references containing citation information of academic literature play an important role as a medium connecting earlier and recent studies. As references contain machine-readable metadata such as author name, title, or publication year, they have been widely used in the field of citation information services including search services for scholarly information and research trend analysis. Many institutions around the world manually extract and continuously accumulate reference metadata to provide various scholarly services. However, manually collection of reference metadata every year continues to be a burden because of the associated cost and time consumption. With the accumulation of a large volume of academic literature, several tools, including GROBID and CERMINE, that automatically extract reference metadata have been released. However, these tools have some limitations. For example, they are only applicable to references written in English, the types of extractable metadata are limited for each tool, and the performance of the tools is insufficient to replace the manual extraction of reference metadata. Therefore, in this study, we focused on constructing a high-quality corpus to automatically extract metadata from multilingual journal article references. Using our constructed corpus, we trained and evaluated a BERT-based transfer-learning model. Furthermore, we compared the performance of the BERT-based model with that of the existing model, GROBID. Currently, our corpus contains 3,815,987 multilingual references, mainly in English and Korean, with labels for 13 different metadata types. According to our experiment, the BERT-based model trained using our corpus showed excellent performance in extracting metadata not only from journal references written in English but also in other languages, particularly Korean. This corpus is available at http://doi.org/10.23057/47.

Mid-term to Long-term Follow-up Results of Reconstruction for Thumb Radial Polydactyly.

BACKGROUND: Preaxial or radial polydactyly is one of the most common hand congenital anomalies in newborns. Contemporary reconstruction methods include ligament reconstruction, excision of the polydactylous thumb, osteotomy, and other surgical techniques according to the type of polydactyly. The purpose of this study was to report mid-term to long-term reconstruction results for thumb (radial) polydactyly. METHODS: We retrospectively reviewed the medical records of patients who underwent reconstruction surgery for preaxial polydactyly. Clinical outcomes, including the range of motion (ROM), pain, and complications, were evaluated. We assessed the final radiographs of the reconstructed thumb to identify the potential development of arthritis or other remaining deformities. After excluding cases without a simple radiograph and cases with a short follow-up period of fewer than 5 years, 26 thumbs were included. The surgical technique followed including excision of polydactylout thumb was tailored to the type of polydactyly. If the nail size of the thumbs was similar, the Bilhaut-Cloquet method was preferred. RESULTS: The mean age of the patients at the surgery and final follow-up was 14.9 months (range: 8 to 30 mo) and 11.9 years (range: 5.8 to 19.3 y), respectively. The mean follow-up was 128.8 months years (range: 60 to 219 mo), and the mean ROM of the thumb was 32.7 and 57.5 degrees in the distal interphalangeal joint (DIP) and metacarpophalangeal (MP) joint, respectively. Ulnar or radial side instability was prominent in 7 patients in the involved joints (26.9%). One patient underwent interphalangeal (IP) fusion for extension lag with pain. The radiologic evaluation revealed that 2 patients developed radiographic evidence of IP joint arthritis (7.7%). Radial deviation of the MP or IP joint existed in 13 cases (range: 5 to 40 degrees) (50.0%), and ulnar deviation of the MP or IP joint existed in 2 cases (range: 19 to 20 degrees) (7.7%). CONCLUSIONS: In mid-term to long-term experience, sequelae such as joint instability, joint stiffness, and remaining deformity cannot be neglected. An unstable MP joint may result if the DIP joint remains stiff or has a lower ROM. LEVEL OF EVIDENCE: Level IV-therapeutic studies.