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Record W2884667255

PDAC 2017: : Growth in attendance signals growing confidence in global minerals sector

2017· article· en· W2884667255 on OpenAlexaboutno aff
Industrial Minerals

Bibliographic record

VenueIndustrial Minerals · 2017
Typearticle
Languageen
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsConventionAttendanceBusinessInvestment (military)Work (physics)Capital (architecture)Government (linguistics)FinanceEngineeringEconomicsGeographyEconomic growthPolitical science
DOInot available

Abstract

fetched live from OpenAlex

[...]this year's gathering saw exhibitor space sold out and increased numbers at investor meetings, short courses and other events, leading PDAC to declare that the 2017 convention exceeded expectations. The 15% tax credit is aimed at helping junior companies raise capital for early stage exploration work, and may be added on top of the 'flow-through share system', allowing exploration companies to transfer costs to the balance sheets of investors, that is also being continued by the Canadian government. PDAC Game changer boasts On the convention floor, exhibitors and attendees alike expressed positive thoughts on future growth for various parts of the industry. Bourassa and his team believe that by the time next year's convention rolls around, Nemaska will be the biggest producer of battery-grade lithium hydroxide in the world. [...]we are one of the solutions.

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 categoriesMeta-epidemiology (narrow)
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 score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.077
GPT teacher head0.282
Teacher spread0.204 · 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.

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
Published2017
Admission routes1
Has abstractyes

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