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Record W4242172089 · doi:10.1109/lgrs.2013.2279724

IEEE Geoscience and Remote Sensing Letters publication information

2013· article· en· W4242172089 on OpenAlexaff
M Crawford, Kamal Sarabandi, Adriano Camps, James Smith, W Vice, T. J. Jackson, J Kerekes Vice, W Moon Vice, Steven C. Reising, William J. Emery, Michael Inggs, M Moghaddam, Motoyuki Sato, Steffen Volz, Lorenzo Bruzzone, Kewei Chen, Gregory Jackson, Wooil M. Moon, Scott Brown, Irena Hajnsek, John P. Kerekes, D Kunkee, D Levine, Jón Atli Benediktsson, Alberto Moreira, Paolo Gamba, Radar Systems, Junbo Shi, Santa California, M Shimoni, Mark A. Sletten, Francesco Soldovieri, Salvatore Stramondo, Pascal Vachon, Greg Wilkinson, Jefferson S. Wong, Synthetic Aperture, Radar Younis, German Aerospace, Peter Staecker, Roberto De Marca, Marko Delimar, John Barr, Gordon W. Day, Michael Lightner, Ralph Ford, Karen Bartleson, Robert Hebner, Marc Apter, José M. F. Moura, Dr Prendergast, Thomas Siegert, Business Administration, Matthew Loeb, Douglas Gorham, Eileen Lach, Betsy Davis, Ieee-Usa Chris Brantley, Alexander Pasik, Information Technology, Patrick Mahoney, Peter Tuohy, Martin Morahan

Bibliographic record

VenueIEEE Geoscience and Remote Sensing Letters · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsCanadian Standards Association
Fundersnot available
KeywordsComputer scienceData scienceEarth scienceRemote sensingInformation retrievalGeology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.510
Threshold uncertainty score0.698

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.5100.298

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 head0.010
GPT teacher head0.196
Teacher spread0.186 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations0
Published2013
Admission routes1
Has abstractno

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