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Record W4281619631 · doi:10.18280/ijsdp.170326

The Concept of Absorbent Environmental Damage in the Context of Civil Responsibility: A Practical Legal Study in the Wetlands of Iraq's Three Major Marshes

2022· article· en· W4281619631 on OpenAlexvenueno aff
Sadkhan Madhloom Bahedh Alabid

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsMarshContext (archaeology)WetlandTortScope (computer science)DamagesEnvironmental planningEnvironmental resource managementEnvironmental scienceLawGeographyEcologyPolitical scienceLiabilityArchaeologyComputer science

Abstract

fetched live from OpenAlex

The research revolves around the idea of assimilation in the sense of assimilating and integrating contractual responsibility within the scope of tort responsibility that causes damage, which is called the first responsibility. The second responsibility is that which is arranged by the existing or competent government or that is entrusted by virtue of legal care, management, and preservation of the environmental site. The study evaluated four locations inside Iraq's southern marshes: the Hammar marsh, which has two sides, western and eastern, resulting in two sites (A and B); the third location, the so-called central marshes, which is group (C); and the fourth location, Al-Hawizeh Marsh, which is group (D). The theorical, scientific analysis is carried out within the scope of the types of assimilation between the components of the environmental site of water, air, and soil in all layers that include concentrations of heavy elements in a manner that changes the acceptable natural amount, such as soil elements, as well as pollutes the water by poisoning or harms the compositional balance of the air. These components (water, soil, and air) are tacked and determined in light of their connection to each other in the environmental site. The damage assimilation is personified by taking samples that determine the forms of pollution. The damage was shown with examples of damage in the first dimension, and the pattern of absorption in the second dimension was used to infer guilt in the second dimension.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.017
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.254
Teacher spread0.231 · 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 designQualitative
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

Citations1
Published2022
Admission routes1
Has abstractyes

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