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Can ChatGPT assist authors with abstract writing in medical journals? Evaluating the quality of scientific abstracts generated by ChatGPT and original abstracts
Get PDFIntroduction
ChatGPT, a sophisticated large language model (LLM), has garnered widespread attention for its ability to mimic human-like communication. As recent studies indicate a potential supportive role of ChatGPT in academic writing, we assessed the LLM’s capacity to generate accurate and comprehensive scientific abstracts from published Randomised Controlled Trial (RCT) data, focusing on the adherence to the Consolidated Standards of Reporting Trials for Abstracts (CONSORT-A) statement, in comparison to the original authors’ abstracts.
Methodology
RCTs, identified in a PubMed/MEDLINE search post-September 2021 across various medical disciplines, were subjected to abstract generation via ChatGPT versions 3.5 and 4, following the guidelines of the respective journals. The overall quality score (OQS) of each abstract was determined by the total number of adequately reported components from the 18-item CONSORT-A checklist. Additional outcome measures included percent adherence to each CONOSORT-A item, readability, hallucination rate, and regression analysis of reporting quality determinants.
Results
Original abstracts achieved a mean OQS of 11.89 (95% CI: 11.23–12.54), outperforming GPT 3.5 (7.89; 95% CI: 7.32–8.46) and GPT 4 (5.18; 95% CI: 4.64–5.71). Compared to GPT 3.5 and 4 outputs, original abstracts were more adherent with 10 and 14 CONSORT-A items, respectively. In blind assessments, GPT 3.5-generated abstracts were deemed most readable in 62.22% of cases which was significantly greater than the original (31.11%; P = 0.003) and GPT 4-generated (6.67%; P<0.001) abstracts. Moreover, ChatGPT 3.5 exhibited a hallucination rate of 0.03 items per abstract compared to 1.13 by GPT 4. No determinants for improved reporting quality were identified for GPT-generated abstracts. Conclusions: While ChatGPT could generate more readable abstracts, their overall quality was inferior to the original abstracts. Yet, its proficiency to concisely relay key information with minimal error holds promise for medical research and warrants further investigations to fully ascertain the LLM’s applicability in this domain
Early detection of Fusarium basal rot infection in onions and shallots based on VOC profiles analysis
Get PDFGas chromatography ion-mobility spectrometry (GC-IMS) technology is drawing increasing attention due to its high sensitivity, low drift, and capability for the identification of compounds. The noninvasive detection of plant pests and pathogens is an application area well suited to this technology. In this work, we employed GC-IMS technology for early detection of Fusarium basal rot in brown onion, red onion, and shallot bulbs and for tracking disease progression during storage. The volatile profiles of the infected and healthy control bulbs were characterized using GC-IMS and gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS). GC-IMS data combined with principal component analysis and supervised methods provided discrimination between infected and healthy control bulbs as early as 1 day after incubation with the pathogen, classification regarding the proportion of infected to healthy bulbs in a sample, and prediction of the infection’s duration with an average R2 = 0.92. Furthermore, GC-TOF-MS revealed several compounds, mostly sulfides and disulfides, that could be uniquely related to Fusarium basal rot infection
Performance of recycled aggregate concrete composite metal decks under elevated temperatures : a comprehensive review
Get PDFThis comprehensive review explores the performance of composite metal decks and structural elements incorporating recycled aggregate concrete (RAC) at elevated temperatures. Despite the acknowledged environmental benefits of using recycled aggregates in concrete production, there is a notable gap in the literature regarding their behaviour under fire conditions. The investigation delves into studies encompassing fire resistance, physio-thermal properties, mechanical attributes, and structural performance of composite metal decks constructed with RAC. The analysis reveals that the inclusion of recycled aggregates has both positive and negative impacts on these elements when exposed to high temperatures. The fire resistance of metal decking composite slabs is significantly influenced by material properties, composition, and RAC mix design. Experimental findings indicate that RAC slabs showed larger midspan deflection under load and fire exposure compared to their counterpart NC slabs. After 120 min. of duration, the mid-span deflection of RAC-0 was recorded to be 19 % higher than the corresponding deflection of NC-0 slab. While temperature-time curves show comparable performance between RAC and natural concrete (NC) slabs, RAC slabs exhibit a notably lower ratio of soffit temperature to the upper surface temperature, resulting in increased spalling. In conclusion, this study advocates for the broader utilization of RAC in constructing structural elements, particularly composite slabs facing extreme temperatures. However, it emphasizes the need for additional research to optimize fire resistance and gain a comprehensive understanding of their behaviour. The findings provide essential guidance for structural engineers and researchers involved in the design of sustainable and fire-resistant structures
From “business as usual” to sustainable “purpose‐driven business”: challenges facing the purpose ecosystem in the United Kingdom and Australia
Get PDFPurpose‐driven businesses have a stated objective to contribute to the welfare of society and the planet alongside generating shareholder value. As interest in purpose‐driven businesses grows, an emerging “purpose ecosystem” of advisers, investors, and enablers offers different types of support for businesses wanting to transition to sustainability. This paper examines how the transition towards purpose‐driven business in Australia and the United Kingdom requires addressing challenges facing this support ecosystem at three levels. First, at the individual level where support providers need to build the capabilities of managers who are experiencing tensions around integrating societal and environmental purpose while facing pressure for maximizing shareholder value. Second, the support providers working within the purpose ecosystem offering professional advice and finance face their own tensions between environmental or social objectives and commercial pressures. Third, there are challenges facing actors in the ecosystems aiming to change the wider policy and institutional environment but facing lobbying from those wanting to keep “business as usual.” We identify practical implications for those parts of the purpose‐driven business ecosystem providing support. This includes building capabilities to combine social, environmental, and commercial purpose; coordination among support providers; and creating an institutional environment to avoid “purpose wash.
The statistical characteristics and auto-regeneration of backflow in non-Newtonian turbulent pipe flow
No full textThe backflow phenomenon in shear-thinning and shear-thickening fluids is investigated in pipe flows at friction Reynolds number Reτ=180 via direct numerical simulations. Conditional average results show that the extreme fluctuation of wall shear stress around the backflow regions is more abrupt under the shear-thinning effect. The statistical characteristics of the backflow at different flow indices from 0.5 to 1.5 show remarkable differences. The probability of the backflow events at the wall increases in both the shear-thinning and the shear-thickening fluids under different mechanisms. The backflow occurs more frequently and exists further away from the wall in the shear-thinning fluids owing to the suppressed near-wall turbulent structures and the laminarization at low flow indices. The increase in the probability of the backflow events in the shear-thickening fluids is caused by increased Q2 and Q4 events in the near-wall region. The variation in the size and the lifespan of the backflow regions with the flow index is very prominent which both increase with the shear-thinning effect and decrease as the flow becomes dilatant. In the weakly turbulent flow of shear-thinning fluid, large backflow regions appear near the leading edge of the turbulent spots where the off-axial turbulent fluctuations are significantly lowered. Observations show the linked evolution between the hairpin vortices and the backflow regions induced underneath the strong spanwise rotations. The backflow follows the auto-regeneration process of the hairpin vortices in a packet which results in coherent streamwise-aligned backflow regions under the hairpin packets confined closer to the wall
Effect of CVI-induced porosity on elastic properties and mechanical behaviour of 2.5D and 3D Cf/SiC composites with multilayered interphase
No full textThe effect of CVI-induced porosity on mechanical behaviour of Cf/SiC composites possessing 2.5D (woven) and 3D (NOOBed) architectures with multilayered (PyC/SiC)n=4 interphase has been investigated. X-ray computed micro-tomography has shown that inter-bundle and inter-fibre pore distribution is influenced by fibre architecture. Elastic constants measured by ultrasound phase spectroscopy have revealed greater anisotropy in 2.5D Cf/SiC composite than 3D Cf/SiC composite. Owing to negligible Cf fraction and flattened inter-bundle pores distributed in thickness direction of 2.5D Cf/SiC composite, the elastic constant, C11 (15±0.03 GPa) is <1/6th of C22 and C33 obtained along fibre directions. Despite the flexural strength of 2.5D Cf/SiC composite (335±8 MPa) being 24% higher than 3D Cf/SiC composite, a more equitable distribution of Cf along three mutually orthogonal directions leads to higher fracture toughness of 3D Cf/SiC composites (~19±1 MPa-m1/2) and greater damage tolerance. Porosity distributions having influence on crack paths, also affect both strength and fracture behaviour
Make hay while the sun shines : an empirical study of maximum price, regret, and trading decisions
No full textTime-constant trading thresholds are optimal for a large class of preferences and asset price dynamics, including Expected Utility and the S-shaped reference-dependent utility of Prospect Theory. Such thresholds imply selling stocks at the maximum price since purchase. We use a large discount brokerage dataset containing US households’ trading records between 1991 and 1996 to document that in 31.6% of cases the stocks sold for a gain are sold on the day when the maximum since purchase occurs. However, not all stocks are sold at a maximum since purchase and the propensity to sell changes depending on how far in time and price the stock is with respect to this past maximum. We find that the propensity to sell initially increases as the price is closer to the past maximum but it then decreases when the price gets in the closest region to the past maximum, leading to an inverse U-shape; and that investors are less likely to sell a gain, the further away in time the maximum price occurred. Studying the joint effect of price and time distance, we find that the propensity to sell is highest at low time distance and high price distance from the maximum since purchase. We relate these findings to regret, belief updating, and attention
Plasma proteomic profiles predict future dementia in healthy adults
No full textThe advent of proteomics offers an unprecedented opportunity to predict dementia onset. We examined this in data from 52,645 adults without dementia in the UK Biobank, with 1,417 incident cases and a follow-up time of 14.1 years. Of 1,463 plasma proteins, GFAP, NEFL, GDF15 and LTBP2 consistently associated most with incident all-cause dementia (ACD), Alzheimer’s disease (AD) and vascular dementia (VaD), and ranked high in protein importance ordering. Combining GFAP (or GDF15) with demographics produced desirable predictions for ACD (area under the curve (AUC) = 0.891) and AD (AUC = 0.872) (or VaD (AUC = 0.912)). This was also true when predicting over 10-year ACD, AD and VaD. Individuals with higher GFAP levels were 2.32 times more likely to develop dementia. Notably, GFAP and LTBP2 were highly specific for dementia prediction. GFAP and NEFL began to change at least 10 years before dementia diagnosis. Our findings strongly highlight GFAP as an optimal biomarker for dementia prediction, even more than 10 years before the diagnosis, with implications for screening people at high risk for dementia and for early intervention
Polymorph identification for flexible molecules : linear regression analysis of experimental and calculated solution- and solid-state NMR data
Get PDFThe Δδ regression approach of Blade et al. [ J. Phys. Chem. A 2020, 124(43), 8959–8977] for accurately discriminating between solid forms using a combination of experimental solution- and solid-state NMR data with density functional theory (DFT) calculation is here extended to molecules with multiple conformational degrees of freedom, using furosemide polymorphs as an exemplar. As before, the differences in measured 1H and 13C chemical shifts between solution-state NMR and solid-state magic-angle spinning (MAS) NMR (Δδexperimental) are compared to those determined by gauge-including projector augmented wave (GIPAW) calculations (Δδcalculated) by regression analysis and a t-test, allowing the correct furosemide polymorph to be precisely identified. Monte Carlo random sampling is used to calculate solution-state NMR chemical shifts, reducing computation times by avoiding the need to systematically sample the multidimensional conformational landscape that furosemide occupies in solution. The solvent conditions should be chosen to match the molecule’s charge state between the solution and solid states. The Δδ regression approach indicates whether or not correlations between Δδexperimental and Δδcalculated are statistically significant; the approach is differently sensitive to the popular root mean squared error (RMSE) method, being shown to exhibit a much greater dynamic range. An alternative method for estimating solution-state NMR chemical shifts by approximating the measured solution-state dynamic 3D behavior with an ensemble of 54 furosemide crystal structures (polymorphs and cocrystals) from the Cambridge Structural Database (CSD) was also successful in this case, suggesting new avenues for this method that may overcome its current dependency on the prior determination of solution dynamic 3D structures