bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.05.06.490896

Expansion of information in scientific research papers

Abstract

Presenting information in papers allows readers to see the evidence for the research claims. The amount of information presented to readers is increasing in high impact factor scientific journals. The aim of the present study was to determine whether there was a similar expansion in the amount of information presented to readers in subject-specific journals. We examined 878 research papers that were published in the journals Biology of Reproduction and Reproduction during the first six months of 1989, 1999, 2009, and 2019. Although there were few differences between the journals, we found that between 1989 and 2019 the number of figures increased 1.5-fold, the number of figure panels increased 3.6-fold, and the number of display items increased 5.6-fold. Amongst the display items, the number of images per paper increased 10-fold, and the number of graphs per paper increased 3.7-fold. The median paper in 1989 was 8 pages long, contained 6 tables and/or figures, with 1 image and 4 graphs. In 2019 the median paper was 12 pages long, contained 7 tables and/or figures, with 13 images and 15 graphs. This expansion of information in subject-specific journals implies that authors, reviewers, and editors need to help readers digest complex biological messages without causing information overload. Lay summaryWe are living in an age of science and information. The amount of information presented in research papers has increased over time in the top science journals. Our research examined whether there has been a similar expansion in information in two influential subject-specific journals. We counted how much information was presented in 878 research papers across a 30-year period in the journals Biology of Reproduction and Reproduction. There were few differences between the two journals. But there was a striking increase in the information presented to readers in 2019 compared with 1989. The typical paper in 1989 was 8 pages long and contained 1 picture and 4 graphs. In 2019 the typical paper was 12 pages long and contained 13 pictures and 15 graphs. This expansion of information means that subject-specific journals must balance the presentation of complex biological messages with the risk of causing information overload.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Abdullaeva, M., Bromfield, J. J., Sheldon, I. M.. 2022-05-06. Expansion of information in scientific research papers. https://doi.org/10.1101/2022.05.06.490896

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Evaluating Large Language Models as Tools to Navigate Researchers in Rapidly Evolving Research Landscapes: A Case Study in Cancer Drug Response Prediction

Large Language Models (LLMs) have emerged as promising tools for assisting researchers in automating and accelerating the synthesis of literature reviews. However, their reliability is a significant concern due to issues like factual inaccuracies and hallucinations. The key question is whether LLMs can reliably provide comprehensive, up-to-date overviews and analyses. This study evaluates the performance of three leading LLMs (OpenAI's ChatGPT, Google's Gemini, and DeepSeek) on the complex task of generating a comprehensive survey paper on deep learning for cancer Drug Response Prediction (DRP). By testing both standard and Deep Research (DR) / Deep Think (DT) modes of LLMs with prompts of varying detail, this paper assesses key academic dimensions, including reference management, content quality, and analytical depth. Key findings reveal that while DR modes of LLMs significantly improve reliability by eliminating hallucinations, performance variations exist across models and prompts. A trade-off between reference quantity and integration quality was observed, and even the best-performing models lacked the analytical depth of human experts, often requiring extensive human supervision. The study concludes that LLMs currently serve as powerful assistive tools but still cannot replace the critical validation and synthesis provided by human researchers. Choosing the best LLM to use depends on the task in hand, while several strategies can be implemented to improve the produced output.

scientific communication and education↗

Attention, Emotion, and Authenticity: Eye-Tracking Evidence from AI vs. Human Visual Design

This study investigates how viewers perceive, attend to, and emotionally respond to AI-generated versus human-created visual content, integrating multimodal data from eye-tracking, facial-coding, and self-report surveys. The sample consisted of 136 undergraduate and graduate students enrolled in a graphic design program at a public university. Participants viewed a series of static and video stimuli produced either by human designers or artificial intelligence systems. Gaze behavior (fixation count, duration, and saccade length), emotional reliability (k-coefficient from RealEye facial-coding), and attitudinal evaluations were analyzed through both parametric and nonparametric statistical tests. The results reveal that human-made visuals elicited longer viewing durations (M = 7035 ms), higher fixation counts (M = 1.44), and broader spatial exploration, suggesting richer semantic and aesthetic engagement. In contrast, AI-generated images produced shorter but more focused attention patterns (M = 4945 ms) and higher but less stable emotional reactions (k = 0.16). The correlation between fixation metrics and affective responses was non-significant ({rho} = -0.015), indicating that cognitive attention and emotional resonance operate as distinct dimensions. Attitudinal data showed a 68.4% accuracy in attributing authorship, with AI visuals often misclassified as human-made reflection of perceptual authenticity bias. Participants described AI content as technically refined yet emotionally limited. These findings suggest that while AI imagery achieves perceptual salience, it still lacks the emotional intentionality and narrative coherence that characterize human creativity.

scientific communication and education↗

Participatory development of innovation and implementation strategy - a practical approach

BackgroundHealthcare and academic institutions face growing challenges in strategic planning due to rapid advances in medicine and technology, alongside fiscal and workforce constraints that limit traditional consultation. Participatory approaches offer a way to integrate diverse stakeholder perspectives under these constraints, generating contextually relevant strategies that can indicate whether current directions are appropriate or whether priorities have been overlooked. MethodsA structured participatory workshop was conducted at the 10th Grampian Research Conference (June 2025). One hundred seventy-eight participants including National Health Service (NHS) staff, academics, industry partners, patients, and public contributors, engaged in 14 parallel roundtable discussions. Contributions were captured using posters and Post-it notes, collecting 148 written annotations. Data were analysed using thematic and content analysis, supplemented by strategic frameworks including Strengths, Weaknesses, Opportunities and Threats (SWOT/TOWS), and Easy Wins, to identify and prioritise actionable strategies. ResultsFive core themes emerged: (1) access to healthcare and services, (2) patient and public involvement and engagement, (3) digital health and service delivery innovation, (4) data access, integration, and governance, and (5) workforce development and culture. SWOT analysis identified strengths in telemedicine, interdisciplinary student training, and patient and public involvement, alongside weaknesses in fragmented data, referral tracking, and workforce pressures. TOWS matrix produced strategy-oriented recommendations such as AI-enabled scheduling, remote monitoring, and transparent referral systems. Easy Wins framework assessment highlighted immediate, low-cost improvements including identifiable NHS caller identification, automated text message reminders, updated informational videos and multilingual materials. ConclusionBy combining participatory outputs with structured strategy tools, this approach demonstrated a resource-efficient model for adaptive planning. The findings align with and extend current national health policy frameworks, offering a replicable approach for institutions aiming to obtain meaningful stakeholder engagement despite fiscal and temporal constraints.

scientific communication and education↗