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Record W4385886115 · doi:10.55274/r0011649

PR676-183606-R03 Remote CP Monitoring Guidelines for an Efficient Use

2020· report· en· W4385886115 on OpenAlexaff
Kevin J. Sunderman

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicSensor Technology and Measurement Systems
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsScope (computer science)Cathodic protectionTask (project management)Benchmark (surveying)Identification (biology)Computer scienceBest practiceSelection (genetic algorithm)Risk analysis (engineering)Systems engineeringEngineeringBusinessArtificial intelligenceGeography

Abstract

fetched live from OpenAlex

The primary objective of this project is to research, identify, evaluate and combine the best industry practices related to remote cathodic protection monitoring, then develop procedures and guidelines for an optimized use of remote cathodic protection monitoring. Included will be rules and recommendations along with a decision tree to aid in selection, optimization and implementation of the most suitable remote cathodic protection monitoring system. There are 3 specific tasks outlined by PRCI in the provided scope of work: - Task 1: Benchmark of Practices - Task 2: Good Practices and Gap Analysis Identification - Task 3: Guidelines and Recommendations

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)0.013
metaresearch head score (Gemma)0.018
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: Methods · Consensus signal: none
Teacher disagreement score0.154
Threshold uncertainty score0.514

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0060.003
Open science0.0040.003
Research integrity0.0060.002
Insufficient payload (model declined to judge)0.1540.179

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 head0.410
GPT teacher head0.403
Teacher spread0.007 · 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
GenreMethods

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

Citations1
Published2020
Admission routes1
Has abstractyes

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