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Record W4288639280 · doi:10.48550/arxiv.1901.03698

Report for the Commission of Inquiry Respecting the Muskrat Falls\n Project

2019· preprint· W4288639280 on OpenAlexaboutno aff
Bent Flyvbjerg, Alexander Budzier

Bibliographic record

VenuearXiv (Cornell University) · 2019
Typepreprint
Language
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsOptimism biasScheduleContext (archaeology)CommissionInvestment (military)HydroelectricityBusinessFinanceOptimismEngineeringEconomicsPolitical scienceManagementGeography

Abstract

fetched live from OpenAlex

This report was commissioned by the Commission of Inquiry Respecting the\nMuskrat Falls Project to provide the national and international context in\nwhich the Muskrat Falls Project took place. The Commission asked for the report\nto cover three specific topics of questions: (1) What is the national and\ninternational context of the Muskrat Falls Project with regards to cost overrun\nand schedule overrun? (What are the typical cost and schedule overruns of\nhydro-electric dam projects? How do hydro-electric dams compare to other\ncapital investment projects? How do Canadian projects compare to other\ncountries?), (2) What are the causes and root causes of cost and schedule\noverruns? (3) What are recommendations, based on international experience and\nresearch into capital investment projects, to prevent cost and schedule\noverruns in hydro-electric dam projects and other capital investment projects?\n Keywords: Hydroelectric Dams, Megaprojects, Cost Overrun, Schedule Overrun,\nOptimism Bias, Strategic Misrepresentation, Infrastructure, Capital Investment\nProjects, Canada, Muskrat Falls\n

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)0.014
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.258
Threshold uncertainty score0.520

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.036
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.001
Scholarly communication0.0070.002
Open science0.0020.003
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0260.005

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 head0.177
GPT teacher head0.273
Teacher spread0.095 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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