OpenAlex observations cover 81.8% of papers in this view

This is an observation-coverage view of The Commonplace’s indexed corpus, not a global ranking. 3055 of 3734 papers have a latest OpenAlex count under the selected filter; 679 do not.

Observed cumulative citations

Papers are ordered by their latest recorded OpenAlex count. Ties use observation date, then title and paper ID for deterministic ordering.

OpenAlex cumulative citation observations for papers in the selected corpus view, ordered by count. Each row shows the provider and observation date; counts from other providers are not added.
Rank in this view	Paper	Published	OpenAlex cumulative citations	Observation
1	Scientists who adopt large language models publish many more preprints — gains of roughly 24–89% depending on field — but much of the extra output is stylistically polished yet substantively weaker. LLM users also draw on a wider, younger literature, forcing journals and funders to rethink how scientific contribution is evaluated. Keigo Kusumegi, Xinyu Yang, Paul Ginsparg, Mathijs de Vaan, Toby Stuart, Yian Yin	January 19, 2026	72	OpenAlex September 5, 2026 provider refresh
2	AI is not a single force: different kinds of systems—predictive, generative, agentic and embodied—alter expertise, authority and coordination in distinct ways; management theory must specify AI types to understand organizational impact. Dominic Chalmers, Richard ‘Rick’ Hunt, Stella Pachidi, Kristina Potočnik, David Townsend	February 10, 2026	33	OpenAlex September 5, 2026 provider refresh
3	AI systems reliably perform narrow clinical tasks and speed routine workflows, but physicians remain indispensable: near-term automation will reallocate tasks rather than replace clinicians, with regulatory, robustness, and liability hurdles slowing widespread substitution. R. Obuchowicz, Adam Piórkowski, Karolina Nurzyńska, B. Obuchowicz, Michał Strzelecki, M. Bielecka	2026	24	OpenAlex September 5, 2026 provider refresh
4	Firms that build AI-enabled dynamic capabilities report better performance largely because AI fosters a data-driven mindset that institutionalizes learning; however, too much reliance on data weakens managers' flexibility and reduces marginal gains. Hassan Samih Ayoub, Joshua Chibuike Sopuru	January 23, 2026	18	OpenAlex September 5, 2026 provider refresh
5	A blueprint for human–AI complementarity: firms that invest in team composition, shared mental models, attention/orchestration, and continuous training can achieve team performance that exceeds humans or AI alone; without these sociotechnical investments, AI’s productivity gains will be limited and uneven. Cleotilde Gonzalez, Kate Donahue, Daniel G Goldstein, Hoda Heidari, Mohammad S. Jalali, Beau G. Schelble, Aarti Singh, Anita Woolley	2026	16	OpenAlex September 5, 2026 provider refresh
6	Hype about AI widens corporate technology gaps at first but can trigger catch-up: modest 'AI washing' suppresses innovation, yet beyond a tipping point firms ramp R&D and narrow the gap; participatory learning eases the harm while high investor sentiment deepens it. Zhe Sun, Yujun Wen, Liang Zhao, Intesar Almugren, Aradhana Galgotia	January 7, 2026	16	OpenAlex September 5, 2026 provider refresh
7	Tax officials say AI tools improve detection and compliance but practical barriers limit impact: a Palestinian revenue department survey finds predictive analytics and automated auditing are seen to boost accuracy, yet concerns over data privacy, high costs and staff unfamiliarity threaten widescale adoption. Abdallah Salah Hasan Alseikh, Murad Ali Ahmad Al-Zaqeba, Izlawanie Muhammad	January 14, 2026	16	OpenAlex September 5, 2026 provider refresh
8	A comprehensive survey finds that the promise of large foundation models for human-AI collaboration depends less on model scale and more on human-centered design, preference-driven objective shaping, and governance; the literature is expanding quickly but remains non-systematic and highlights open challenges in bias, evaluation, and socio-economic effects. Vanshika Vats, Marzia Binta Nizam, Minghao Liu, Ziyuan Wang, Richard Ho, Mohnish Sai Prasad, Vincent Titterton, Sai Venkat Malreddy, Riya Aggarwal, Yanwen Xu, Lei Ding, Jay Mehta, Nathan Grinnell, Li Liu, Sijia Zhong, Devanathan Nallur Gandamani, Xinyi Tang, Rohan Ghosalkar, Celeste Shen, Rachel Shen, Nafisa Hussain, Kesav Ravichandran, James Davis	August 22, 2026	13	OpenAlex September 5, 2026 provider refresh
9	A survey of 627 studies identifies four distinct AI–human decision-making paradigms driven by AI–human dynamics and decision typologies; the framework helps organizations choose between intuitive, algorithmic, analytical and hybrid decision modes as they integrate AI into operations. Han Li, Feng Tian	April 3, 2026	13	OpenAlex September 5, 2026 provider refresh
10	AI can raise radiology accuracy and throughput, but benefits are conditional on real-world integration—poorly designed deployments risk automation bias, deskilling and workflow disruption that can erode clinical and economic gains. B. Koçak, Renato Cuocolo	2026	10	OpenAlex September 5, 2026 provider refresh
11	AI sharpens the lens on ESG reporting—transformer-based NLP scales comparability and flags potential greenwashing—but evidence that managerial deployment of AI actually boosts stakeholder trust or market outcomes is scarce, and language and explainability shortfalls constrain practical use. Jiacheng Liu, Ye Yuan, Zhelun Zhu	January 9, 2026	10	OpenAlex September 5, 2026 provider refresh
12	Bench tests show SAP IBP excels under stable conditions but is slow to adapt when demand turns volatile; custom AI planning engines reconfigure faster, reduce planner effort and facilitate quicker scenario exploration. Divya Soundarapandian	January 1, 2026	10	OpenAlex September 5, 2026 provider refresh
13	Clear, high-quality data builds trust in AI decision-support systems, and that trust helps drive organizations' intentions to adopt them; those intentions correlate with higher self-reported decision-making efficiency. G. Bondac, S. Stanescu, C. Ionescu, Anisoara Duica, Marilena Carmen Uzlău	2026	10	OpenAlex September 5, 2026 provider refresh
14	Countries with stronger AI readiness record notably better progress on the Sustainable Development Goals, and FinTech and Blockchain activity also predict higher SDG performance; when nations develop multiple digital technologies together, the combined sustainability gains exceed the sum of individual effects. Nesrine Gafsi, Amina Hamdouni, Aida Smaoui	March 4, 2026	10	OpenAlex September 5, 2026 provider refresh
15	Passive, copy-based use of AI erodes workers' confidence, ownership and sense of meaningful work — and some harms persist after returning to manual tasks; by contrast, active, draft-first collaboration with AI preserves worker agency and avoids these psychological costs. Elena Hayoung Lee, Yidan Yin, Nan Jia, Cheryl Wakslak	March 15, 2026	10	OpenAlex September 5, 2026 provider refresh
16	Academic research on AI credit scoring delivers strong predictive results but treats fairness and explainability as separate issues, leaving scarce guidance for regulated, real‑world use; the literature rarely evaluates integrated approaches that meet oversight and accountability requirements. Rashed Bahlool, Nabil Hewahi, Wael Elmedany	February 3, 2026	9	OpenAlex September 5, 2026 provider refresh
17	Detailed message-level analysis of 19 verified harm cases finds frequent chatbot misrepresentations of sentience and numerous user expressions of suicidal ideation and delusional thinking, with harmful dynamics amplifying over long multi-turn conversations — a pattern that raises regulatory, liability and product-design concerns for LLM providers. Jared Moore, Ashish Mehta, William Agnew, Jacy Reese Anthis, Ryan Louie, Yifan Mai, Peggy Yin, Myra Cheng, Samuel J Paech, Kevin Klyman, Stevie Chancellor, Eric Lin, Nick Haber, Desmond C. Ong	March 17, 2026	9	OpenAlex September 5, 2026 provider refresh
18	A practical risk-based playbook for government AI: classify systems by impact and require accountability, human oversight, impact assessments, fairness testing, secure audit trails and enforceable procurement clauses for high-risk uses; a phased roadmap helps resource-constrained administrations deploy beneficial AI while protecting rights and trust. NAVEED RAFAQAT AHMAD	January 10, 2026	8	OpenAlex September 5, 2026 provider refresh
19	A shift to genuinely multi-hazard, multi-risk disaster management is both practicable and worthwhile, but meaningful uptake needs coordinated progress on methods, usable tools, equity, local coproduction and early-career capacity. Without standardized concepts, stronger spatio-temporal evidence, and operationally tested decision-support systems, benefits will remain patchy and context-dependent. Philip J. Ward, Sophie Buijs, Roxana Ciurean, Judith Claassen, James Daniell, Kelley De Polt, Melanie Duncan, Stefania Gottardo, Stefan Hochrainer-Stigler, Robert Šakić Trogrlić, Julius Schlumberger, Timothy Tiggeloven, Silvia Torresan, Nicole van Maanen, Andrew Warren, Carmen D. Carmen D. Álvarez-Albelo, Vanessa Banks, Benjamin Blanz, Veronica Casartelli, Jordan Correa, Julia Crummy, Anne Sophie Daloz, Marleen C. de Ruiter, Juan Jose Diaz-Hernandez, Jaime Díaz-Pacheco, Pedro Dorta Antequera, Davide Mauro Ferrario, David Geurts, Sara García-González, Joel C. Gill, Raúl Hernández-Martín, Wiebke Jäger, Abel López Díez, Lin Ma, Jaroslav Myšiak, Diep Ngoc Nguyen, Noemi Padrón Fumero, Eva-Cristina Petrescu, Karina Reiter, Jana Sillmann, Lara Smale, Tristian Stolte	March 11, 2026	8	OpenAlex September 5, 2026 provider refresh
20	AI raises demand for advanced technical skills but heightens job insecurity where reskilling and participatory governance are absent; firms that combine targeted human-capital investment with transparent governance see lower resistance and smoother implementation. Lorena Arranz Lahuerta, María Rosa López Ramajo, Andrés Gandía	2026	8	OpenAlex September 5, 2026 provider refresh
21	AI-enabled forecasting and intelligent dispatch can materially raise revenues, extend life and cut emissions for grid-scale batteries, improving levelized cost of storage and payback times; however, most claimed gains stem from simulations and isolated demos, and scaling them requires better data, lighter algorithms and market rules that reward speed and degradation-aware operation. N. Ketjoy, Y. Muna, M. Kaewpanha, Wisut Chamsa-ard, Tawat Suriwong, C. Termritthikun	2026	8	OpenAlex September 5, 2026 provider refresh
22	AI adoption in Chinese cities is associated with measurable cuts in pollution and carbon emissions (estimated coefficient -0.026), working through improved energy efficiency, industrial restructuring and more green innovation; effects are strongest in some inland and Beijing–Tianjin–Hebei agglomerations and weaker or insignificant in major coastal manufacturing regions. Mengyu Li, Tangfa Liu, Guancheng Wu, Ji Lin, Bingnan Guo	January 13, 2026	7	OpenAlex September 5, 2026 provider refresh
23	AI and other new digital skills are appearing in roughly one in ten vacancies in advanced economies and pay a clear wage premium. Yet their spread is linked to sharper labor-market polarization—helping high-skilled workers while hollowing out middle-skilled roles and reducing employment in AI‑exposed occupations with low worker complementarity, with young workers hit especially hard. Florence Jaumotte, Jaden Kim, David Koll, Elmer Li, Longji Li, Giovanni Melina, Alina Song, Marina Mendes Tavares	2026	7	OpenAlex September 5, 2026 provider refresh
24	In ASEAN banks, robust ESG strategies raise risk‑adjusted lending returns outright, whereas AI pays off only when it tightens credit‑risk discipline; stricter supervisors magnify both effects. Mohammed R. M. Salem	January 2, 2026	7	OpenAlex September 5, 2026 provider refresh
25	In nine emerging markets, good governance is the transmission belt through which generative-AI readiness boosts national financial performance; once dynamics and endogeneity are accounted for, governance quality fully mediates the AI–finance link. Bahaa Awwad, Mohammad A. A. Zaid, Adel Sarea	January 22, 2026	7	OpenAlex September 5, 2026 provider refresh

Showing the first 25 of 3055 observed papers.

Publication-year context

Citation counts generally accumulate over time. Cohort medians use observed OpenAlex counts only, while the observed and missing columns keep the full corpus denominator visible.

Paper coverage and median observed OpenAlex cumulative citations by publication year.
Publication year	Corpus papers	Observed	Missing	Median observed citations
2026	3734	3055	679	0

How to read these counts

Counts are cumulative provider observations captured on the displayed dates. Citation practices differ by field and publication age, and provider coverage changes over time. These counts do not establish quality, correctness, causal influence, or societal impact.

Review coverage quality for corpus limitations and the intake pipeline documentation for how The Commonplace collects and assesses research.