MétaCan
Menu
Back to cohort
Record W4391404629 · doi:10.1002/fsh.11053

A Field Guide to Fishes of the Salish Sea: Puget Sound and the Straits of Georgia and Juan de Fuca, Washington State and British Columbia T. W. Pietsch and J. W. Orr. Illustrated by J. R. Tomelleri. Published by Chatwin Books. 2023. 372 pages. US$36.00 (Paperback)

2024· article· en· W4391404629 on OpenAlexaffabout
Pete Castillo, Brittnie Spriel, B.J. Maher, Nathanael John Tabert, Talen Rimmer, Francis Juanes

Bibliographic record

VenueFisheries · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSound (geography)OceanographyState (computer science)FisheryGeographyEnvironmental ethicsArchaeologyGeologyBiologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

FisheriesVolume 49, Issue 3 p. 141-142 Book Review A Field Guide to Fishes of the Salish Sea: Puget Sound and the Straits of Georgia and Juan de Fuca, Washington State and British Columbia , T. W. Pietsch and J. W. Orr. Illustrated by J. R. Tomelleri. Published by Chatwin Books. 2023. 372 pages. US$36.00 (Paperback) Pete Castillo, Pete Castillo [email protected] School of Environmental Studies, University of Victoria, David Turpin Building, B243, Victoria, BC, V8W 2Y2 CanadaSearch for more papers by this authorBrittnie Spriel, Brittnie Spriel Department of Biology, University of Victoria, Victoria, BC, CanadaSearch for more papers by this authorBridget Maher, Bridget Maher Department of Biology, University of Victoria, Victoria, BC, CanadaSearch for more papers by this authorNathanael Tabert, Nathanael Tabert Department of Biology, University of Victoria, Victoria, BC, CanadaSearch for more papers by this authorTalen Rimmer, Talen Rimmer Department of Biology, University of Victoria, Victoria, BC, CanadaSearch for more papers by this authorFrancis Juanes, Francis Juanes Fisheries Book Reviews Editor orcid.org/0000-0001-7397-0014 Department of Biology, University of Victoria, Victoria, BC, CanadaSearch for more papers by this author Pete Castillo, Pete Castillo [email protected] School of Environmental Studies, University of Victoria, David Turpin Building, B243, Victoria, BC, V8W 2Y2 CanadaSearch for more papers by this authorBrittnie Spriel, Brittnie Spriel Department of Biology, University of Victoria, Victoria, BC, CanadaSearch for more papers by this authorBridget Maher, Bridget Maher Department of Biology, University of Victoria, Victoria, BC, CanadaSearch for more papers by this authorNathanael Tabert, Nathanael Tabert Department of Biology, University of Victoria, Victoria, BC, CanadaSearch for more papers by this authorTalen Rimmer, Talen Rimmer Department of Biology, University of Victoria, Victoria, BC, CanadaSearch for more papers by this authorFrancis Juanes, Francis Juanes Fisheries Book Reviews Editor orcid.org/0000-0001-7397-0014 Department of Biology, University of Victoria, Victoria, BC, CanadaSearch for more papers by this author First published: 31 January 2024 https://doi.org/10.1002/fsh.11053Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume49, Issue3March 2024Pages 141-142 RelatedInformation

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)0.000
metaresearch head score (Gemma)0.001
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 score0.931
Threshold uncertainty score0.848

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2530.199

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 head0.189
Teacher spread0.182 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueFisheriesSame topicMaritime and Coastal ArchaeologyFrench-language works237,207