MétaCan
Menu
Back to cohort
Record W1600686206

損害賠償 豫定額의 職權減額上 參酌의 基準時와 參酌 事由 - 부동산 매매계약에 있어서 ‘解除 후 時價의 變動’이 참작사유로 될 수 있는가? (대상판례 : 2004. 12. 10. 선고 2002다73852) -

2005· article· ko· W1600686206 on OpenAlexaboutno aff
김제완

Bibliographic record

Venue민사법학 · 2005
Typearticle
Languageko
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsnot available
Fundersnot available
KeywordsSupreme courtReal estateDatabase transactionLawBusinessLaw and economicsPolitical scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

This article is on the liquidated damage and the mitigation in Korean civil law. In a real estate sale transaction case in which a buyer made a breach of the contract but the seller resold it to the 3rd party so successfully that the seller recovered more than he lost, the Korean Supreme court held that the liquidated damage should be limited to 50% considering his recovery. The author is of opinion that the seller might recover the liquidate damage in full in spite of the fluctuation of the market price. The author is mentioning the duty of mitigation, the assessment of damage, the time of the assessment of damage in Canadian law and other related common law cases in a perspective of comparative legal studies.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.009
Scholarly communication0.0070.005
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0160.003

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 head0.030
GPT teacher head0.313
Teacher spread0.283 · 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 designNot applicable
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
Published2005
Admission routes1
Has abstractyes

Explore more

Same venue민사법학Same topicLegal principles and applicationsFrench-language works237,207