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Record W2903427766 · doi:10.1080/07038992.2018.1517022

Assessing the Benefits of Simulated RADARSAT Constellation Mission Polarimetry Images for Structural Mapping of an Impact Crater in the Canadian Shield

2018· article· en· W2903427766 on OpenAlexaffvenueabout
Mary‐Anne Fobert, J. G. Spray, V. Singhroy

Bibliographic record

VenueCanadian Journal of Remote Sensing · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsNatural Resources CanadaUniversity of New Brunswick
Fundersnot available
KeywordsConstellationImpact craterPolarimetryRemote sensingShieldGeographyGeologyCartographyAstrobiologyAstronomyPhysicsOpticsPaleontology

Abstract

fetched live from OpenAlex

Traditional polarization architectures transmit and receive linear polarizations (LL). Canada’s RADARSAT Constellation Mission (RCM) will be equipped with a hybrid architecture that will transmit a circular polarization and receive linear polarizations (CL). The objective of this study is to assess the benefits of CL polarization images, in comparison to LL, for automated structural mapping in Canadian Shield terrain. RADARSAT-2 data acquired over the Manicouagan impact crater are used to simulate RCM data through the Natural Resources Canada RCM-CP (compact polarimetric) v3 program. Circular transmit/receive (CC) polarization images were also generated and included in this study. The structural mapping benefits of each polarization architecture have been assessed via comparisons with a manually inferred fault map, escarpment map, and optical data illustrating faults indicated through extended linear waterbodies. The results demonstrate that the CL and LL architectures provide a complementary overview of the structural geology. CL, in relation to LL, provides a greater spatial extent of lineaments, better optimizes faults expressed through linear waterbodies, and highlights the largest number of manually inferred faults, while LL better recognizes faults related to moderate relief. We conclude that RCM’s CL architecture will provide an additional benefit for structural mapping in the Canadian Shield and equivalent terrains.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.038
GPT teacher head0.294
Teacher spread0.255 · 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 designSimulation or modeling
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

Citations4
Published2018
Admission routes3
Has abstractyes

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