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Preface

2017· book-chapter· en· W4385975187 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionArtVisual artsSection (typography)Art historyComputer science

Abstract

fetched live from OpenAlex

Extract It is just 100 years since the publication of the book which started the area of enquiry that has become known as Sensory Ecology. That book was The Fundus Oculi of Birds, written by the Canadian-born clinician, Casey Albert Wood. At the time of its publication Wood was Professor of Ophthalmology at the University of Illinois. Although he was a clinician, he had a passion for birds and he managed to combine his two interests in this book. A recent exhibition, ‘The Bird Man of McGill’, was promoted by the rare books and special collections section of McGill University. It presented information on Wood’s life and his many interests. Wood gave his personal archive and collections to the University and now the exhibition can be readily browsed in digital form at http://digital.library.mcgill.ca/caseywood/. Casey Wood employed a comparative approach to the study of birds’ eyes. Using relatively simple techniques, he examined and described the eyes of a wide range of bird species held in various zoos. He viewed the eyes of live birds through a hand lens or an ophthalmoscope, and he also examined whole retinas of excised eyes using a microscope. Wood recorded in drawings, and in paintings executed by Arthur Head, some of the diversity in structures found in the retinas of birds. The book was of a large format and took as its inspiration some drawings published 20 years earlier by J.R Slonaker in a paper titled, ‘A comparative study of the areas of acute vision in vertebrates’ in the Journal of Morphology. Remarkably illustrations from both Slonaker and Wood still have value to anyone wishing to start describing the diversity of birds’ eyes and also for anyone wishing to provide a framework that accounts for this diversity in both functional and ecological terms.

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)0.005
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 score0.713
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.7130.507

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 head0.018
GPT teacher head0.223
Teacher spread0.205 · 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
Published2017
Admission routes1
Has abstractyes

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