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Record W4404717224 · doi:10.1080/01431161.2024.2412807

Preface: the role of space ocean science and technology towards sustainable development goal

2024· article· en· W4404717224 on OpenAlexaff
Kumar Nimit, Nurul Hazrina Idris, Cara Wilson, C. Gabriel, Gad Levy, Jim Gower, Ming‐An Lee, Sidhartha Sahoo, Stefano Vignudelli

Bibliographic record

VenueInternational Journal of Remote Sensing · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsSpace (punctuation)Sustainable developmentEnvironmental resource managementComputer scienceEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

This is the editorial/preface of the special issue featuring a selection of research papers presented at the 15th Biennial Pan Ocean Remote Sensing Conference (PORSEC), which was also the first ever PORSEC to conduct online tutorials as well as first during the UN Ocean Decade (2021–30). In this background, we also revisit the state of ocean remote sensing through analysis of 20,973 research documents identified from SCOPUS databases published through 1967–2023, as a contribution to the UN Ocean Decade.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.140

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.252
Teacher spread0.247 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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