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Record W2762724400 · doi:10.3366/anh.2017.0445

The contribution of Henry Charles Williamson (1871–1949) to Scottish and Canadian fisheries research

2017· article· en· W2762724400 on OpenAlexaboutno aff
P. G. Moore

Bibliographic record

VenueArchives of Natural History · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Biodiversity
Canadian institutionsnot available
Fundersnot available
KeywordsHerringFish <Actinopterygii>FisherySettlement (finance)Biology

Abstract

fetched live from OpenAlex

The Scottish zoologist Henry Charles Williamson was one of a group of young men who initiated fisheries science in the late Victorian age, schooled under Professor William Carmichael McIntosh at St Andrews University. Initially working for the Fishery Board of Scotland, Williamson contributed original studies on fish anatomy, morphology, systematics and life cycles; decapod Crustacea life-history stages; fish diseases and parasites. He was at the forefront of attempts to transport herring ova to Australia and New Zealand to introduce this European food fish to antipodean waters. That involved him researching how to retard development of ova using low temperatures and developing glass settlement-plate techniques for their transportation. He left Scotland in 1925 to spend five years in the Canadian Pacific, studying salmon migration by tagging and latterly becoming responsible for pilchard and herring work there too. Returning to his home town of Dundee in retirement, he lived a quiet life, giving talks to local groups, supporting his church's administration and contributing articles to the fishermen's press. Sadly he died before he could complete the two volumes on fishes that he was in the course of writing.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.236
Teacher spread0.214 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2017
Admission routes1
Has abstractyes

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