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Record W2917273547

An estimation of farmland prices in Romania after the application of law 17 of 2014.

2018· article· en· W2917273547 on OpenAlexaboutno aff
Lucian Luca

Bibliographic record

VenueAgricultural Economics and Rural Development · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsEstimationAgricultural economicsLand priceAgricultureQuarter (Canadian coin)Land ValuesValue (mathematics)Agricultural landEconomicsGeographyLand useStatisticsMathematicsEcology
DOInot available

Abstract

fetched live from OpenAlex

The paper presents an estimate of the average national price of agricultural land, for the years 2014 (second half), 2015, 2016 and 2017 (the first three quarters). Throughout the investigated period, the average price was about 4000 euro/ha. For this estimation, the public data on the sale offers of agricultural land outside the localities were used, for parcels larger than 30 ha. For the comparison with the prices of parcels smaller than 30 ha, the average price in the third quarter of 2017 was also estimated, for three counties (Bacău, Olt and Mureş). The results confirm the experts’ perception of the price gaps between the small-sized parcels and the large-sized parcels, the value of the latter being almost double. The analysis also highlights the differences between the farmland prices in the counties with high agricultural potential, from the plain area, where the number of transactions with consolidated land is also higher, compared to the counties from the hilly area, where prices are lower.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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.

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
Published2018
Admission routes1
Has abstractyes

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