MétaCan
Menu
Back to cohort

Environmental and operational safety of tailing storage facilities: analysis of accidents, causes and technical state diagnostic methods

2023· article· en· W4387193345 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnvironmental Safety and Natural Resources · 2023
Typearticle
Languageen
FieldEngineering
TopicMining and Gasification Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsChinaPopulationEnvironmental protectionGeographyEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

A number of high-profile industrial accidents occurred at sludge and tailings storage facilities in different countries of the world are considered. The problem of ecological and technogenic danger of operating such objects, which leads to significant casualties among the civilian population, serious economic losses and harms the surrounding natural environment, is illustrated. The main causes of emergency situations have been established and analysed, it will help to reduce the risk of accidents and to minimize negative environmental consequences for similar facilities in Ukraine. The retrospective review covers the period from 1960 to 2022. During this time, about 150 cases of soil dams’ destruction in waste storage facilities were recorded. The different tendency in the frequency of accidents is noted. In particular, during the period from 1960 to 2009, there were 98 accidents with an average frequency of nearly two (1.98) per year. Over the last decade (2010-2020), the number of accidents reached 36 cases, and their frequency almost doubled to 3.6 accidents per year. Over the past two years, from the beginning of 2021 to December 2022, 10 accidents have already been registered. The vast majority of accidents during this period occurred in 34 countries of the world. The largest number of them was noted in the USA (22.4%), China (10.4%), Brazil (7.5%), Chile (6.7%), the Philippines (6.0%), Canada (5.2 %), Great Britain (4.5%) and other countries. Studies note jumps in the increase of accidents that have ten-year trends (1975, 1985, 1995, 2005). The general tendency of mass accidents since the beginning of 2015 is shown, which is substantiated by the expired terms of operation of many mining and ore enterprises (mines) and significant (exceeding normative) terms of operation of tailings storage facilities, which in some places were left without proper supervision and care. It was established that a violation of the dam slope stability (37%), an overflow of the designed capacity of the tailings storage facility (12%), seismic activity (11%), etc., are the main causes of accidents. A review of modern approaches to the management of dangerous anthropogenic objects and methods of diagnosing the technical condition of such structures was conducted. The use of a complex of organizational and technical solutions about the implementing the modern methods of assessment and control the technical condition of waste storage facilities at various levels of their operation and stages of the life cycle is proposed.

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.

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 score0.653
Threshold uncertainty score0.524

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 head0.008
GPT teacher head0.239
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