Gustavious Williams

Brigham Young University

Subject Areas: Hydrology, informatics., error metrics, Great Salt Lake

 Recent Activity

ABSTRACT:

This resource contains the code, notebooks, pinned software environment, regenerated training samples, validation outputs, run manifest and provenance records, annual conifer-area tables, derived GeoTIFFs, figures, and comparison-run evidence supporting the analysis of coniferous forest change in tributary basins of the Great Salt Lake, Utah, USA, from 1986–2025. The analysis uses Landsat Collection 2 Level-2 surface reflectance, National Land Cover Database training labels, a 100-member random-forest ensemble, and a fixed 30 m EPSG:5070 analysis grid. The deposited materials reproduce the reported area estimates, accuracy assessment, spatial agreement and change products, and trend analyses. Public source datasets are not redistributed; their use and provenance are documented in the notebooks and run records. Earth Engine asset identifiers are retained as provenance for the completed run but are not transferable to other accounts. The README provides the archive structure, software setup, and instructions for adapting the code to a reuser’s own Earth Engine project.

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ABSTRACT:

Companion data deposit for Williams (2026, Water (MDPI), manuscript water-4402795, in review). Contains the deduplicated bibliometric corpus (1,470 records from Web of Science, Scopus, and ProQuest; abstract text omitted per publisher terms), the curated per-cluster outputs that back every numeric finding in the manuscript (S1-S8 supplementary tables, network metrics, LDA topic-modeling results, AI-assisted thematic annotations), a per-cluster evidence bundle, a redacted record of the large-language-model prompts used for cluster annotation, VOSviewer-format network exports, and a snapshot of the R analysis pipeline.

Version 2 (2026-07) restages the deposit for the Water revision round 1. The bibliographic-coupling pipeline was re-run from the final 1,470-record corpus; the coupling subset (1,012 records), community count (379), singleton count (342), and eligible-cluster count (14) all changed from version 1, as did the cluster identifiers. Cluster annotations were regenerated with Claude Opus 5 (Anthropic, accessed 2026-07-28).

See the top-level README.md and per-subdirectory READMEs for column-level metadata and the "Not runnable as written" notes on the code snapshot.

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ABSTRACT:

Companion data deposit for Williams (2026, Limnology and Oceanography, in review). Contains the deduplicated bibliometric corpus (1,470 records from Web of Science, Scopus, and ProQuest; abstract text omitted per publisher terms), the curated per-cluster outputs that back every numeric finding in the manuscript (S1-S8 supplementary tables, network metrics, LDA topic-modeling results, AI-assisted thematic annotations), per-cluster evidence bundle, VOSviewer-format network exports, and a snapshot of the R analysis pipeline. See the top-level README.md and per-subdirectory READMEs for column-level metadata and the "Not runnable as written" notes on the code snapshot.

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ABSTRACT:

Companion data deposit for Williams (2026, Limnology and Oceanography, in review). Contains the deduplicated bibliometric corpus (1,470 records from Web of Science, Scopus, and ProQuest; abstract text omitted per publisher terms), the curated per-cluster outputs that back every numeric finding in the manuscript (S1-S8 supplementary tables, network metrics, LDA topic-modeling results, AI-assisted thematic annotations), per-cluster evidence bundle, VOSviewer-format network exports, and a snapshot of the R analysis pipeline. See the top-level README.md and per-subdirectory READMEs for column-level metadata and the "Not runnable as written" notes on the code snapshot.

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Resource Resource

ABSTRACT:

Companion data deposit for Williams (2026, Water (MDPI), manuscript water-4402795, in review). Contains the deduplicated bibliometric corpus (1,470 records from Web of Science, Scopus, and ProQuest; abstract text omitted per publisher terms), the curated per-cluster outputs that back every numeric finding in the manuscript (S1-S8 supplementary tables, network metrics, LDA topic-modeling results, AI-assisted thematic annotations), a per-cluster evidence bundle, a redacted record of the large-language-model prompts used for cluster annotation, VOSviewer-format network exports, and a snapshot of the R analysis pipeline.

Version 2 (2026-07) restages the deposit for the Water revision round 1. The bibliographic-coupling pipeline was re-run from the final 1,470-record corpus; the coupling subset (1,012 records), community count (379), singleton count (342), and eligible-cluster count (14) all changed from version 1, as did the cluster identifiers. Cluster annotations were regenerated with Claude Opus 5 (Anthropic, accessed 2026-07-28).

See the top-level README.md and per-subdirectory READMEs for column-level metadata and the "Not runnable as written" notes on the code snapshot.

Show More
Resource Resource

ABSTRACT:

This resource contains the code, notebooks, pinned software environment, regenerated training samples, validation outputs, run manifest and provenance records, annual conifer-area tables, derived GeoTIFFs, figures, and comparison-run evidence supporting the analysis of coniferous forest change in tributary basins of the Great Salt Lake, Utah, USA, from 1986–2025. The analysis uses Landsat Collection 2 Level-2 surface reflectance, National Land Cover Database training labels, a 100-member random-forest ensemble, and a fixed 30 m EPSG:5070 analysis grid. The deposited materials reproduce the reported area estimates, accuracy assessment, spatial agreement and change products, and trend analyses. Public source datasets are not redistributed; their use and provenance are documented in the notebooks and run records. Earth Engine asset identifiers are retained as provenance for the completed run but are not transferable to other accounts. The README provides the archive structure, software setup, and instructions for adapting the code to a reuser’s own Earth Engine project.

Show More