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Record W4389473801 · doi:10.1002/agt2.474

From bud to blossom: The incredible journey of <i>Aggregate</i>

2023· article· en· W4389473801 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAggregate · 2023
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsAggregate (composite)Impact factorCitationDirectoryScopusQuality (philosophy)Library scienceComputer sciencePolitical scienceNanotechnologyPhysicsMaterials scienceLaw

Abstract

fetched live from OpenAlex

The days are long, but the years are short. This quote perfectly encapsulates my feelings as we mark the third anniversary of Aggregate. Over the past 3 years, Aggregate has been a steadfast companion to scientists, growing together with them in the field of research on aggregate science. On June 28, 2023, Clarivate Analytics unveiled Journal Citation Reports (JCR) 2023 and Aggregate received its first Journal Impact Factor (JIF) of 18.8. This is a great milestone in the development of Aggregate. I am thrilled to witness that Aggregate has made further progress this year in terms of both the quantity and quality of published papers. The inauguration of Aggregate 3 years ago was a rather brave attempt. I am happy to see that it has been developing on a fast track. After being included in the Directory of Open Access Journals and the Emerging Sources Citation Index, Aggregate has been indexed by Scopus (a database run by Elsevier) this year. In 2022, Aggregate obtained its first JCR, with a Q1 ranking in three categories: Chemistry, Multidisciplinary; Chemistry, Physical; and Materials Science, Multidisciplinary. This year, Aggregate stayed at the top and obtained its first JIF of 18.8, manifesting that the journal has attracted a wide spectrum of audience in the scientific community. Aggregate is rapidly growing: while the data for 2023 are not yet available, the number of articles published in 2022 was increased by 70% from that in 2021. At Aggregate, we recognize the importance of maintaining a balance between quantity and quality. We do not just take the JIF as the sole measure of success. Instead, we prioritize the leadership position of the journal in its field of study. We believe that quality and impact of the published papers will naturally contribute to the continued growth and influence of Aggregate. As an open access journal, Aggregate is committed to promoting widespread utilization of research findings. Starting from December of this year, Aggregate will introduce the Article Processing Charges to ensure that researchers and scholars worldwide have free access to the published papers. We believe that this transition will facilitate the quick dissemination of knowledge and contribute to the advancement of scientific research across disciplines. We greatly appreciate the support and understanding of our authors and readers as we make this transition. We remain dedicated to maintaining the highest standards of quality and integrity in the review and publication processes, and we will continue to foster a collaborative and inclusive environment where researchers can share their latest discoveries and insights in a timely manner. To keep close communication with our readers and bring cutting-edge research findings to the public, we regularly promote high-quality papers published in Aggregate through social media such as Twitter (@AggregateOA) and WeChat (@Aggregate_2020). We have also organized a number of onsite and online academic events. Following the successful hosting of three global online webinars on soft matter, electroluminescence, and protein science in the US, UK, and Australia, respectively, in 2022, this year, we have organized another three webinars on luminescent materials, smart materials, and bioengineering. We have further witnessed the flourishing of onsite conferences and meetings alongside regular regional online webinars in China. This summer, the first editorial board meeting of Chinese members was successfully held in Tengchong, Yunnan, and an Aggregate summit forum took place in Wuhan, Hubei. We organized a journal forum on nanobiology during the ChinaNanomedicine 2023 conference in Guangzhou, Guangdong. All these events have garnered tremendous success. I am delighted to announce that we have welcomed three young Associate Editors to our team. They are Prof. Eric Rivard from University of Alberta (Canada), Prof. Wei Tao from Harvard Medical School (US), and Prof. Ali K. Yetisen from Imperial College London (UK). We highly value the growth of young talents. Building upon the success of our first Emerging Investigators Special Issue last year, we have expanded our Next Generation Board, which now comprises 36 young researchers worldwide. In October of this year, Elsevier and Stanford University published a data update for “updated science-wide author databases of standardized citation indicators”, identifying the “World's Top 2% Scientists 2023”. We are proud to see that 98 scholars from Aggregate Editorial Board have been included in this esteemed list. In November, Clarivate Analytics released the “Highly Cited Researchers 2023”, wherein 47 members from Aggregate Editorial Board were recognized. The growth of Aggregate would not have been possible without the dedicated efforts of our authors, reviewers, readers, and editorial board members. Herein, I extend my heartfelt gratitude to all who have supported and contributed to the development of our journal. Aggregate has emerged as a leading platform for forefront aggregology studies. Looking ahead, I am excited about the bright future of Aggregate. We will continue to uphold the highest scientific standards and provide a large stage for groundbreaking discoveries and innovative insights. Together, we have established a premier journal in aggregate science, and I am confident that our collective endeavors will continue to shape the field in the years to come. The author declares no conflict of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0240.232
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0040.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.007

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.510
GPT teacher head0.541
Teacher spread0.032 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it