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Record W4252676140 · doi:10.1016/s0026-0657(06)70607-5

Inco banks $1bn as record earnings rocket 35 per cent

2006· article· en· W4252676140 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

VenueMetal Powder Report · 2006
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsRedressTailingsBusinessHazardEarningsHuman healthGovernment (linguistics)Environmental planningEnvironmental protectionEnvironmental scienceNatural resource economicsEnvironmental healthFinanceEcology

Abstract

fetched live from OpenAlex

Responsible mining companies have done much to redress the environmental damage of earlier technologies and continue to do more. In the Sudbury Basin, one of the most important mining areas in the world, both Inco Limited and Falconbridge Limited, two of the largest nickel producers, have significantly decreased sulphur dioxide emissions in the last 40 years from substantially 100% to about 10% or less of the sulphur in the ore; decreased water effluents by recycling; treated effluents to comply with government regulations; revegetated mine rock and surface tailings deposits and rehabilitated landscapes in the surrounding communities. Inco and Falconbridge continue to develop improved means for environmentally sound handling of all wastes including recycling and to reclaim land at abandoned mine sites. They have developed and implemented environmental policies and codes of practice, not only to comply with regulations, but to anticipate them. The mining industry recognises the need for regulation to protect human health and the environment. Existing regulations are based on a hazard assessment approach. A more realistic, pragmatic and cost-effective basis for regulation is risk management. This relates any documented effects to measured exposures and recognizes the need for exposure levels low enough that incidence of adverse health effects is as low as in the surrounding ecosystem.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.772

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)0.0010.000

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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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