MétaCan
Menu
Back to cohort
Record W4367296941 · doi:10.33002/jelp03.01.01

Flyrock Throw Calculations Unscientific and Unreliable – The “Hits” Just Keep on Coming

2023· article· en· W4367296941 on OpenAlexvenueno aff
Tony Sevelka

Bibliographic record

VenueJournal of Environmental Law & Policy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
Fundersnot available
KeywordsEasementBusinessExplosive materialTrespassLiabilityProperty (philosophy)Computer securityRock blastingForensic engineeringRisk analysis (engineering)EngineeringLawComputer sciencePolitical scienceMining engineeringFinance

Abstract

fetched live from OpenAlex

Flyrock is the dirty little secret of the aggregate industry and its explosives engineers, and they have been remarkably successful in concealing the potentially deadly consequences of flyrock from the public, while continuing to engage in reckless blasting practices based on theoretical guesswork rather than proven practical land use planning safeguards such as permanent (fixed) onsite setbacks (excavation limits) coupled with permanent offsite separation distances from existing and potential future sensitive land uses. Flyrock is an unavoidable by-product of blasting rock, and has the potential to damage personal or real property, injure, permanently disable or kill humans and non-humans, both onsite and offsite. Flyrock, along with other adverse effects such as vibrations, that leaves the boundaries of an aggregate operation, constitutes nuisance and trespass, and damage or injury caused by detonation of explosives, should be held to strict liability. Implementing proactive and forward-looking land use policies that safeguard existing and envisioned sensitive land uses from the potentially deadly consequences of detonation of explosives in aggregate extraction is the most effective way to protect the long-term health, safety and welfare of existing and future generations, and to avoid interfering with the use and enjoyment of third-party real property.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.102
GPT teacher head0.340
Teacher spread0.238 · 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 designTheoretical or conceptual
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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Environmental Law & PolicySame topicClimate Change, Adaptation, MigrationFrench-language works237,207