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Record W4360598346 · doi:10.15659/uzalcbs2022.12793

SÜRDÜRÜLEBİLİR TARIM EKSENİNDE UZAKTAN ALGILAMA TABANLI TARIM TAKİP MODELİ YAKLAŞIMI

2022· article· tr· W4360598346 on OpenAlexaff
Ali YILDIRIM, Şeyma Yıldız, A. Yaşar KÜRKÇÜ, Yağmur IŞLAK, Kahraman KALKAN, Yasin ÇAM, I. Yalcin, Mehmet DOĞRULUK

Bibliographic record

Venuenot available
Typearticle
Languagetr
FieldSocial Sciences
TopicHistorical Turkish Studies
Canadian institutionsIntertek (Canada)
Fundersnot available
KeywordsTarim riverGeologyGeomorphology

Abstract

fetched live from OpenAlex

Günümüzde iklim değişikliğinin ve diğer küresel faktörlerin (nüfus artışı, göçler vb.) oluşturduğu riskler, tarımsal üretimin sürdürülebilir şekilde devam etmesini büyük bir ihtiyaç haline getirmiştir.Bu kapsamda birçok ülke ve uluslararası organizasyon, tarımsal üretimin desteklenmesine yönelik tarım politikaları geliştirmektedir.Bu doğrultuda, ülkemizde de çeşitli kurumlar tarımsal üretimi doğrudan ya da dolaylı olarak desteklemektedir.Tarım desteklerinin planlanmasında ise temel dayanak tarımsal üretime

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0060.003
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0260.003

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 head0.042
GPT teacher head0.295
Teacher spread0.253 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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Same topicHistorical Turkish StudiesFrench-language works237,207