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Record W2016918833 · doi:10.2113/gseegeosci.14.1.54

Investigation, Remediation and Protection of Land Resources

2008· article· en· W2016918833 on OpenAlexaboutno aff
R. E. Jackson

Bibliographic record

VenueEnvironmental and Engineering Geoscience · 2008
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsCitationIconDownloadSubject (documents)Environmental remediationWorld Wide WebLibrary scienceComputer scienceEngineeringEcology

Abstract

fetched live from OpenAlex

Book Review| February 01, 2008 Investigation, Remediation and Protection of Land Resources Richard E. Jackson Richard E. Jackson 1INTERA Engineering Ltd., Heidelberg, Ontario, N0B 1Y0, Canada Search for other works by this author on: GSW Google Scholar Environmental & Engineering Geoscience (2008) 14 (1): 54–55. https://doi.org/10.2113/gseegeosci.14.1.54 Article history first online: 02 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share MailTo Twitter LinkedIn Tools Icon Tools Get Permissions Search Site Citation Richard E. Jackson; Investigation, Remediation and Protection of Land Resources. Environmental & Engineering Geoscience 2008;; 14 (1): 54–55. doi: https://doi.org/10.2113/gseegeosci.14.1.54 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyEnvironmental & Engineering Geoscience Search Advanced Search The title of this most interesting book reflects the evolution of the practice of engineering geology to the subject matter of this journal, Environmental and Engineering Geoscience. Dieter Genske has taught at a number of European universities and is the author of the 2005 Springer textbook Ingenieurgeologie: Grundlagen und Anwendung (Engineering Geology: Fundamentals & Applications). From the extensive reference list at the end of the book, it is clear that Dr. Genske has worked extensively during this decade on the topic of this book—the characterization and rehabilitation of contaminated and disused urban landscapes. Because we in North... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

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)0.001
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0340.023

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 head0.008
GPT teacher head0.134
Teacher spread0.126 · 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
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
Published2008
Admission routes1
Has abstractyes

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