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At least 73 records · Page 4

Predictive Indicators of the Performance of Large Language Models

In several mission contexts, it is desirable to estimate the performance of large language models (LLMs) on tasks that we cannot run directly. In light of published “scaling laws” our hypothesis is that some tasks should be consistently more challenging than others based on characteristics of the task. The goal of this project was to begin quantifying how much information about LLM performance can be gained from the features of a model and a task. Two of our statistical models struggled to converge. Pass/fail test results may provide limited information for inference beyond model quality and task difficulty, but we see no evidence at this time for significant feature interaction effect sizes, arguing for simple models. Future work extending the models to capitalize on perplexity of ground truth answers is suggested. This project also introduces “Depth of Knowledge Variant Testing” as a strategy for more finely assessing language models on open domain question and answer tasks. We developed sets of questions that ask a language model to produce similar information while demonstrating increasing depth of knowledge, and also relabeled existing Q&A test questions with their depth of knowledge. Our results suggest further consideration of Bloom’s taxonomy and further refinement of prompts to properly elicit information at varying depths. In the course of this work, we set up a basic infrastructure for standardizing tasks and testing many language models on these tasks. In addition to testing the predictive quality of model features and performance across test suites, with this project we have introduced two new task features to contextualize each test question: the Dewey Classification main category of information covered, and the Bloom’s taxonomy level that corresponds to the depth of knowledge probed by the question. Splits across these and other features produced over five hundred task subtypes with distinct feature vectors, which we tested on half a dozen models.

97 MATHEMATICS AND COMPUTING↗

IMG/VR v4: an expanded database of uncultivated virus genomes within a framework of extensive functional, taxonomic, and ecological metadata

Viruses are widely recognized as critical members of all microbiomes. Metagenomics enables large-scale exploration of the global virosphere, progressively revealing the extensive genomic diversity of viruses on Earth and highlighting the myriad of ways by which viruses impact biological processes. IMG/VR provides access to the largest collection of viral sequences obtained from (meta)genomes, along with functional annotation and rich metadata. A web interface enables users to efficiently browse and search viruses based on genome features and/or sequence similarity. Here, for this work, we present the fourth version of IMG/VR, composed of >15 million virus genomes and genome fragments, a ≈6-fold increase in size compared to the previous version. These clustered into 8.7 million viral operational taxonomic units, including 231 408 with at least one high-quality representative. Viral sequences in IMG/VR are now systematically identified from genomes, metagenomes, and metatranscriptomes using a new detection approach (geNomad), and IMG standard annotation are complemented with genome quality estimation using CheckV, taxonomic classification reflecting the latest taxonomic standards, and microbial host taxonomy prediction. IMG/VR v4 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.

59 BASIC BIOLOGICAL SCIENCES↗

vConTACT: an iVirus tool to classify double-stranded DNA viruses that infect Archaea and Bacteria

Taxonomic classification of archaeal and bacterial viruses is challenging, yet also fundamental for developing a predictive understanding of microbial ecosystems. Recent identification of hundreds of thousands of new viral genomes and genome fragments, whose hosts remain unknown, requires a paradigm shift away from traditional classification approaches and towards the use of genomes for taxonomy. Here we revisited the use of genomes and their protein content as a means for developing a viral taxonomy for bacterial and archaeal viruses. A network-based analytic was evaluated and benchmarked against authority-accepted taxonomic assignments and found to be largely concordant. Exceptions were manually examined and found to represent areas of viral genome ‘sequence space’ that are under-sampled or prone to excessive genetic exchange. While both cases are poorly resolved by genome-based taxonomic approaches, the former will improve as viral sequence space is better sampled and the latter are uncommon. Finally, given the largely robust taxonomic capabilities of this approach, we sought to enable researchers to easily and systematically classify new viruses. Thus, we established a tool, vConTACT, as an app at iVirus, where it operates as a fast, highly scalable, user-friendly app within the free and powerful CyVerse cyberinfrastructure.

59 BASIC BIOLOGICAL SCIENCES↗

Four principles to establish a universal virus taxonomy

A universal taxonomy of viruses is essential for a comprehensive view of the virus world and for communicating the complicated evolutionary relationships among viruses. However, there are major differences in the conceptualisation and approaches to virus classification and nomenclature among virologists, clinicians, agronomists, and other interested parties. Here, we provide recommendations to guide the construction of a coherent and comprehensive virus taxonomy, based on expert scientific consensus. Firstly, assignments of viruses should be congruent with the best attainable reconstruction of their evolutionary histories, i.e., taxa should be monophyletic. This fundamental principle for classification of viruses is currently included in the International Committee on Taxonomy of Viruses (ICTV) code only for the rank of species. Secondly, phenotypic and ecological properties of viruses may inform, but not override, evolutionary relatedness in the placement of ranks. Thirdly, alternative classifications that consider phenotypic attributes, such as being vector-borne (e.g., “arboviruses”), infecting a certain type of host (e.g., “mycoviruses,” “bacteriophages”) or displaying specific pathogenicity (e.g., “human immunodeficiency viruses”), may serve important clinical and regulatory purposes but often create polyphyletic categories that do not reflect evolutionary relationships. Nevertheless, such classifications ought to be maintained if they serve the needs of specific communities or play a practical clinical or regulatory role. However, they should not be considered or called taxonomies. Finally, while an evolution-based framework enables viruses discovered by metagenomics to be incorporated into the ICTV taxonomy, there are essential requirements for quality control of the sequence data used for these assignments. Combined, these four principles will enable future development and expansion of virus taxonomy as the true evolutionary diversity of viruses becomes apparent.

59 BASIC BIOLOGICAL SCIENCES↗

A new taxonomy for distributed computer systems based upon operating system structure

Characteristics of the resource structure found in the operating system are considered as a mechanism for classifying distributed computer systems. Since the operating system resources, themselves, are too diversified to provide a consistent classification, the structure upon which resources are built and shared are examined. The location and control character of this indivisibility provides the taxonomy for separating uniprocessors, computer networks, network computers (fully distributed processing systems or decentralized computers) and algorithm and/or data control multiprocessors. The taxonomy is important because it divides machines into a classification that is relevant or important to the client and not the hardware architect. It also defines the character of the kernel O/S structure needed for future computer systems. What constitutes an operating system for a fully distributed processor is discussed in detail.

Foudriat, E. C.↗

Filovirus RefSeq Entries: Evaluation and Selection of Filovirus Type Variants, Type Sequences, and Names

Sequence determination of complete or coding-complete genomes of viruses is becoming common practice for supporting the work of epidemiologists, ecologists, virologists, and taxonomists. Sequencing duration and costs are rapidly decreasing, sequencing hardware is under modification for use by non-experts, and software is constantly being improved to simplify sequence data management and analysis. Thus, analysis of virus disease outbreaks on the molecular level is now feasible, including characterization of the evolution of individual virus populations in single patients over time. The increasing accumulation of sequencing data creates a management problem for the curators of commonly used sequence databases and an entry retrieval problem for end users. Therefore, utilizing the data to their fullest potential will require setting nomenclature and annotation standards for virus isolates and associated genomic sequences. The National Center for Biotechnology Information’s (NCBI’s) RefSeq is a non-redundant, curated database for reference (or type) nucleotide sequence records that supplies source data to numerous other databases. Building on recently proposed templates for filovirus variant naming [<virus name> (<strain>)/<isolation host-suffix>/<country of sampling>/<year of sampling>/<genetic variant designation>-<isolate designation>], we report consensus decisions from a majority of past and currently active filovirus experts on the eight filovirus type variants and isolates to be represented in RefSeq, their final designations, and their associated sequences.

Mononegavirales↗

Phylogenomics and the first higher taxonomy of Placozoa, an ancient and enigmatic animal phylum

Placozoa is an ancient phylum of extraordinarily unusual animals: miniscule, ameboid creatures that lack most fundamental animal features. Despite high genetic diversity, only recently have the second and third species been named. While prior genomic studies suffer from incomplete placozoan taxon sampling, we more than double the count with protein sequences from seven key genomes and produce the first nuclear phylogenomic reconstruction of all major placozoan lineages. This leads us to the first complete Linnaean taxonomic classification of Placozoa, over a century after its discovery: This may be the only time in the 21st century when an entire higher taxonomy for a whole animal phylum is formalized. Our classification establishes 2 new classes, 4 new orders, 3 new families, 1 new genus, and 1 new species, namely classes Polyplacotomia and Uniplacotomia; orders Polyplacotomea, Trichoplacea, Cladhexea, and Hoilungea; families Polyplacotomidae, Cladtertiidae, and Hoilungidae; and genus Cladtertia with species Cladtertia collaboinventa, nov. Our likelihood and gene content tree topologies refine the relationships determined in previous studies. Adding morphological data into our phylogenomic matrices suggests sponges (Porifera) as the sister to other animals, indicating that modest data addition shifts this node away from comb jellies (Ctenophora). Furthermore, by adding the first genomic protein data of the exceptionally distinct and branching Polyplacotoma mediterranea , we solidify its position as sister to all other placozoans; a divergence we estimate to be over 400 million years old. Yet even this deep split sits on a long branch to other animals, suggesting a bottleneck event followed by diversification. Ancestral state reconstructions indicate large shifts in gene content within Placozoa, with Hoilungia hongkongensis and its closest relatives having the most unique genetics.

54 ENVIRONMENTAL SCIENCES↗

Characteristic variations in reflectance of surface soils

Surface soil samples from a wide range of naturally occurring soils were obtained for the purpose of studying the characteristic variations in soil reflectance as these variations relate to other soil properties and soil classification. A total 485 soil samples from the U.S. and Brazil representing 30 suborders of the 10 orders of 'Soil Taxonomy' was examined. The spectral bidirectional reflectance factor was measured on uniformly moist soils over the 0.52 to 2.32 micron wavelength range with a spectroradiometer adapted for indoor use. Five distinct soil spectral reflectance curve forms were identified according to curve shape, the presence or absence of absorption bands, and the predominance of soil organic matter and iron oxide composition. These curve forms were further characterized according to generically homogeneous soil properties in a manner similar to the subdivisions at the suborder level of 'Soil Taxonomy'. Results indicate that spectroradiometric measurements of soil spectral bidirectional reflectance factor can be used to characterize soil reflectance in terms that are meaningful to soil classification, genesis, and survey.

Stoner, E. R.↗

Feedback and Oscillations: Constructing Feedback Systems for Root Cause Analysis of Oscillations in Power Grids

Dynamic phenomena linked to inverter-based resources (IBRs) have gained global attention. Several IBR-induced dynamics have caused bulk power system-connected wind or solar power plants to trip, and some have even led to widespread outages. In addition, many oscillations have been observed involving IBR power plants. In 2023, the IEEE Power & Energy Society (PES) IBR Subsynchronous Oscillations (SSO) task force published a journal article, “Real-World Subsynchronous Oscillation Events in Power Grids With High Penetrations of Inverter-Based Resources,” in which 19 IBR oscillation events were examined for their causation. Earlier in 2020, another PES task force article, “Definition and Classification of Power System Stability-Revisited & Extended,” authored by prominent academics, introduced converter-driven stability as a new category of stability. The international power grid industry community also took action by publishing the CIGRE Green Book, Power System Dynamic Modelling and Analysis in Evolving Networks (led by Babak Badrzadeh and Zia Emin) in 2024. In August 2024, the Energy Systems Integration Group (ESIG) released a practical guide led by Nick Miller, “Diagnosis and Mitigation of Observed Oscillations in IBR-Dominant Power System: A Practical Guide.” The goal of the guide is to assist practicing engineers in making initial judgments and conducting detailed analyses about oscillations. Finally, when addressing the classification of stability and oscillations, the guide emphasizes a causality-based taxonomy for grouping, such as voltage control-induced oscillations, synchronization-induced oscillations, and frequency or active power control-induced oscillations.

Fan, Lingling [Univ. of South Florida, Tampa, FL (↗

An Evolutionary System of Mineralogy: Proposal for A Classification of Planetary Materials Based on Natural Kind Clustering

Minerals reveal the nature of the co-evolving geosphere and biosphere through billions of years of Earth history. Mineral classification systems have the potential to elucidate this rich evolutionary story; however, the present mineral taxonomy, based as it is on idealized major element chemistry and crystal structure, lacks a temporal aspect, and thus cannot reflect planetary evolution. A complementary evolutionary system of mineralogy based on the quantitative recognition of “natural kind clustering” for a wide range of condensed planetary materials with different paragenetic origins has the potential to amplify, though not supersede, the present classification system.

Philosophy of mineralogy↗

Cowpox virus: What’s in a Name?

Traditionally, virus taxonomy relied on phenotypic properties; however, a sequence-based virus taxonomy has become essential since the recent requirement of a species to exhibit monophyly. The species Cowpox virus has failed to meet this requirement, necessitating a reexamination of this species. Here, we report the genomic sequences of nine Cowpox viruses and, by combining them with the available data of 37 additional genomes, confirm polyphyly of Cowpox viruses and find statistical support based on genetic data for more than a dozen species. These results are discussed in light of the current International Committee on Taxonomy of Viruses species definition, as well as immediate and future implications for poxvirus taxonomic classification schemes. Data support the recognition of five monophyletic clades of Cowpox viruses as valid species.

species delimitation↗

Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification

Accurate metagenomic classification relies on comprehensive, up-to-date, and validated reference databases. While the NCBI BLAST Nucleotide (nt) database, encompassing a vast collection of sequences from all domains of life, represents an invaluable resource, its massive size—currently exceeding 10 12 nucleotides—and exponential growth pose significant challenges for researchers seeking to maintain current nt-based indices for metagenomic classification. Recognizing that no current nt-based indices exist for the widely used Centrifuge classifier, and the last public version currently available was released in 2018, we addressed this critical gap by leveraging advanced high-performance computing resources. We present new Centrifuge-compatible nt databases, meticulously constructed using a novel pipeline incorporating different quality control measures, including reference decontamination and filtering. These measures demonstrably reduce spurious classifications, as shown through our reanalysis of published metagenomic data where Plasmodium annotations were dramatically reduced using our decontaminated database, highlighting how database quality can significantly impact research conclusions. Through temporal comparisons, we also reveal how our approach minimizes inconsistencies in taxonomic assignments stemming from asynchronous updates between public sequence and taxonomy databases. These discrepancies are particularly evident in taxa such as Listeria monocytogenes and Naegleria fowleri, where classification accuracy varied significantly across database versions. These new databases, made available as pre-built Centrifuge indexes, respond to the need for an open, robust, nt-based pipeline for taxonomic classification in metagenomics. Applications such as environmental metagenomics, forensics, and clinical metagenomics, which require comprehensive taxonomic coverage, will benefit from this resource. Our work highlights the importance of treating reference databases as dynamic entities, subject to ongoing quality control and validation akin to software development best practices. This approach is crucial for ensuring accuracy and reliability of metagenomic analysis, especially as databases continue to expand in size and complexity.

59 BASIC BIOLOGICAL SCIENCES↗

Bridging Theory with Practice: An Exploratory Study of Visualization Use and Design for Climate Model Comparison

Evaluation methodologies in visualization have mostly focused on how well the tools and techniques cater to the analytical needs of the user. While this is important in determining the effectiveness of the tools and advancing the state-of-the-art in visualization research, a key area that has mostly been overlooked is how well established visualization theories and principles are instantiated in practice. This is especially relevant when domain experts, and not visualization researchers, design visualizations for analysis of their data or for broader dissemination of scientific knowledge. There is very little research on exploring the synergistic capabilities of cross-domain collaboration between domain experts and visualization researchers. To fill this gap, in this paper we describe the results of an exploratory study of climate data visualizations conducted in tight collaboration with a pool of climate scientists. The study analyzes a large set of static climate data visualizations for identifying their shortcomings in terms of visualization design. The outcome of the study is a classification scheme that categorizes the design problems in the form of a descriptive taxonomy. The taxonomy is a first attempt for systematically categorizing the types, causes, and consequences of design problems in visualizations created by domain experts. We demonstrate the use of the taxonomy for a number of purposes, such as, improving the existing climate data visualizations, reflecting on the impact of the problems for enabling domain experts in designing better visualizations, and also learning about the gaps and opportunities for future visualization research. We demonstrate the applicability of our taxonomy through a number of examples and discuss the lessons learnt and implications of our findings.

54 ENVIRONMENTAL SCIENCES↗

Craters on Earth, Moon, and Mars - Multivariate classification and mode of origin

Testing extraterrestrial craters and candidate terrestrial analogs for morphologic similitude is treated as a problem in numerical taxonomy. According to a principal-components solution and a cluster analysis, 402 representative craters on the Earth, the Moon, and Mars divide into two major classes of contrasting shapes and modes of origin. Craters of net accumulation of material (cratered lunar domes, Martian calderas, and all terrestrial volcanoes except maars and tuff rings) group apart from craters of excavation (terrestrial meteorite impact and experimental explosion craters, typical Martian craters, and all other lunar craters). Maars and tuff rings belong to neither group but are transitional. The classification criteria are four independent attributes of topographic geometry derived from seven descriptive variables by the principal-components transformation. Morphometric differences between crater bowl and raised rim constitute the strongest of the four components.

Pike, R. J.↗

CONSTRUCTION OF A CALIBRATED PROBABILISTIC CLASSIFICATION CATALOG: APPLICATION TO 50k VARIABLE SOURCES IN THE ALL-SKY AUTOMATED SURVEY

With growing data volumes from synoptic surveys, astronomers necessarily must become more abstracted from the discovery and introspection processes. Given the scarcity of follow-up resources, there is a particularly sharp onus on the frameworks that replace these human roles to provide accurate and well-calibrated probabilistic classification catalogs. Such catalogs inform the subsequent follow-up, allowing consumers to optimize the selection of specific sources for further study and permitting rigorous treatment of classification purities and efficiencies for population studies. Here, we describe a process to produce a probabilistic classification catalog of variability with machine learning from a multi-epoch photometric survey. In addition to producing accurate classifications, we show how to estimate calibrated class probabilities and motivate the importance of probability calibration. We also introduce a methodology for feature-based anomaly detection, which allows discovery of objects in the survey that do not fit within the predefined class taxonomy. Finally, we apply these methods to sources observed by the All-Sky Automated Survey (ASAS), and release the Machine-learned ASAS Classification Catalog (MACC), a 28 class probabilistic classification catalog of 50,124 ASAS sources in the ASAS Catalog of Variable Stars. We estimate that MACC achieves a sub-20% classification error rate and demonstrate that the class posterior probabilities are reasonably calibrated. MACC classifications compare favorably to the classifications of several previous domain-specific ASAS papers and to the ASAS Catalog of Variable Stars, which had classified only 24% of those sources into one of 12 science classes.

79 ASTRONOMY AND ASTROPHYSICS↗

A three-parameter asteroid taxonomy

Broadband U, V, and x photometry together with IRAS asteroid albedos have been used to construct an asteroid classification system. The system is based on three parameters (U-V and v-x color indices and visual geometric albedo), and it is able to place 96 percent of the present sample of 357 asteroids into 11 taxonomic classes. It is noted that all but one of these classes are analogous to those previously found using other classification schemes. The algorithm is shown to account for the observational uncertainties in each of the classification parameters.

Tedesco, Edward F.↗

Radio galaxy zoo EMU: towards a semantic radio galaxy morphology taxonomy

We present a novel natural language processing (NLP) approach to deriving plain English descriptors for science cases otherwise restricted by obfuscating technical terminology. We address the limitations of common radio galaxy morphology classifications by applying this approach. We experimentally derive a set of semantic tags for the Radio Galaxy Zoo EMU (Evolutionary Map of the Universe) project and the wider astronomical community. We collect 8486 plain English annotations of radio galaxy morphology, from which we derive a taxonomy of tags. The tags are plain English. The result is an extensible framework, which is more flexible, more easily communicated, and more sensitive to rare feature combinations, which are indescribable using the current framework of radio astronomy classifications.

79 ASTRONOMY AND ASTROPHYSICS↗