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Record W4360598305 · doi:10.15659/uzalcbs2022.13032

FOTOGRAMETRİK NOKTA BULUTLARINDAN MAKİNE ÖĞRENMESİ YÖNTEMİ İLE BİNA ÇIKARIMI

2022· article· tr· W4360598305 on OpenAlexaff
Onur Can Bayrak, Melis Uzar

Bibliographic record

Venuenot available
Typearticle
Languagetr
FieldArts and Humanities
TopicCultural and Sociopolitical Studies
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsMathematics

Abstract

fetched live from OpenAlex

Fotogrametrik yntemlerle retilen nokta bulutlar, objelere ait renk ve 3 boyutlu konum bilgisini iermesi sayesinde yeryzne ait karakteristiklerin gsteriminde kullanlmaktadr.Ancak retilen nokta bulutlarndaki arazi kullanm snflarnn tespit edilebilmesi iin 3 boyutlu saysallatrma ileminin yaplmas gerekmektedir.Bu ilemin zaman alc olmas ve hedef blgenin boyutuna gre donanm problemleri ile karlalmasndan dolay hedef

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), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0060.001
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0410.001

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 head0.063
GPT teacher head0.247
Teacher spread0.184 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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