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PREFACE: TECHNICAL COMMISSION III

2020· article· en· W3047548045 on OpenAlexaff
Jie Jiang, Ahmed Shaker, H. Zhang

Bibliographic record

VenueISPRS annals of the photogrammetry, remote sensing and spatial information sciences · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRemote sensingLibrary scienceCommissionGeographyCartographyComputer scienceEngineeringPolitical science

Abstract

fetched live from OpenAlex

Abstract. The work of ISPRS Technical Commission III is devoted to remote sensing. For the XXIVth ISPRS CONGRESS, Technical Commission III received total 603 submissions 216 full papers and 387 abstracts. Among these submissions 107 are accepted as peer-reviewed contributions for publication in the ISPRS Annals, 218 were accepted for publication in the ISPRS Archives. There are 228 accepted submissions were withdrawn by authors due to the postpone of the Congress and other reasons.These papers are dedicated mostly to topics of the 10 TC III working groups and 4 inter-commission working groups as follows – WG III/1: Thematic Information Extraction; WG III/2: Microwave Remote Sensing; WG III/3: SAR-based Surface Generation and Deformation Monitoring; WG III/4: Hyperspectral Image Processing; WG III/5: Information Extraction from LiDAR Intensity Data; WG III/6: Remote Sensing Data Fusion; WG III/7: Landuse and Landcover Change Detection; WG III/8: Remote Sensing of Atmospheric Environment; WG III/9: Cryosphere and Hydrosphere; WG III/10: Agriculture and Natural Ecosystems Modelling and Monitoring; ICWG III/II: Planetary Remote Sensing and Mapping; ICWG III/Iva: Disaster Assessment, Monitoring and Management; ICWG III/IVb: Remote Sensing Data Quality; ICWG III/IVc: Environment and Health. The papers and abstracts were evaluated by the experts in the field and Working Group Chairs according to content, significance, originality, relevance, and clearness of presentation.We would like to thank the authors for their contributions, the reviewers for their reviewing, the working group officers for their efforts on calling for papers, and the organizers of the Congress for publishing this volume.

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)0.001
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 score0.996
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.058
GPT teacher head0.280
Teacher spread0.223 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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