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Record W3088312462 · doi:10.35414/akufemubid.746252

Global ve Bölgesel (Yüksek Çözünürlüklü) Sayısal Yükseklik Modellerinin Doğruluk Analizi Üzerine Bir İnceleme

2020· article· tr· W3088312462 on OpenAlexaff
Bihter Erol, Mustafa Serkan Ișık, Serdar Erol

Bibliographic record

VenueAfyon Kocatepe University Journal of Sciences and Engineering · 2020
Typearticle
Languagetr
FieldEngineering
TopicSynthetic Aperture Radar (SAR) Applications and Techniques
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsPhysicsMathematicsHumanitiesArt

Abstract

fetched live from OpenAlex

Topografik ykseklikler birok mhendislik uygulamasnda ve yerbilimlerine ilikin aratrmalarda kullanlmaktadr. Yksek znrlkl Saysal Ykseklik Modelleri (SYM), gnmzde ykseklik verilerini elde etmenin en pratik ve ekonomik yoludur. SYM'lerinin retiminde farkl yntemler

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.565
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.013
GPT teacher head0.196
Teacher spread0.182 · 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.

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAfyon Kocatepe University Journal of Sciences and EngineeringSame topicSynthetic Aperture Radar (SAR) Applications and TechniquesFrench-language works237,207