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Record W4212775239 · doi:10.1029/2021ea002140

Near‐Surface Geophysics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

2022· article· en· W4212775239 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEarth and Space Science · 2022
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInteroperabilityIconComputer scienceData sharingWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract Pointing to the Integrated, Coordinated, Open, Networked Findability, Accessibility, Interoperability, and Reusability (ICON‐FAIR) principles, we have determined several opportunities for implementation within the realm of near‐surface geophysics (NSG), representing a broad range of data acquisition and processing technologies. Our work explores the multifaceted community‐driven nature of NSG and, by applying ICON‐FAIR principles, we identify three key strategic objectives: (i) the development of an approach to integrating NSG into other geoscience data collection projects, (ii) the creation of coordinated and open standardized NSG data, and (iii) the networking of post‐secondary institutions to foster an equipment sharing consortium. The precedence within the geoscientific community demonstrates that there are significant opportunities for advancing interdisciplinary applications of NSG through the implementation of structural change within the ICON‐FAIR framework.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.255
Teacher spread0.244 · 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