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Record W7132161316

Meliorace - Skuteč - 2014

2014· article· cs· W7132161316 on OpenAlexaboutno aff
T. (Tomáš) Fabiánek

Bibliographic record

VenueASEP · 2014
Typearticle
Languagecs
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsHyperspectral imagingGeoreferenceUSableImage resolutionImaging spectroscopyReflectivityData acquisitionSpectral resolution
DOInot available

Abstract

fetched live from OpenAlex

The main interest was to map a drainage system in an agricultural landscape. For this purpose airborne hyperspectral imaging sensor (CASI), which operates in the visible spectral region, was chosen. CASI (ITRES Inc. Canada) is an essential part of Flying Laboratory of Imaging Spectroscopy (FLIS) operated by the Center for global change research AS CR, v. v. i. Image acquisition was carried out during the growing season 2014, in the high spatial resolution (0.5 m) containing spectral information within 48 bands in the range 400-1000 nm. Scanned data were georeferenced in the UTM WGS84 33N map projection, radiometrically and atmospherically corrected. Therefore, the reflectance is without of the influence of the atmosphere and the resulting image is fully usable for required analyzes

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 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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.054
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0540.052

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 head0.003
GPT teacher head0.190
Teacher spread0.187 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2014
Admission routes1
Has abstractyes

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