MétaCan
Menu
Back to cohort
Record W3172212630 · doi:10.1162/leon_r_02039

The Birth of the Idea of Photography

2021· article· en· W3172212630 on OpenAlexaboutno aff
Stephen Petersen

Bibliographic record

VenueLeonardo · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsnot available
Fundersnot available
KeywordsIconCitationPhotographyArt historyComputer scienceLibrary scienceArtVisual arts

Abstract

fetched live from OpenAlex

June 02 2021 The Birth of the Idea of Photography The Birth of the Idea of Photography. By François Brunet; translated by Shane B. Lillis. (Cambridge, MA, U.S.A.: MIT Press; Toronto, Canada: RIC Books, 2019. First published as Le naissance de l'idée de photographie, 2000. 304 pp., illus. Trade. ISBN: 978-0262043267.) Stephen Petersen Stephen Petersen Search for other works by this author on: This Site Google Scholar Author and Article Information Stephen Petersen Online Issn: 1530-9282 Print Issn: 0024-094X ©2021 ISAST2021ISAST Leonardo (2021) 54 (3): 357–359. https://doi.org/10.1162/leon_r_02039 Connected Content A correction has been published: Erratum: The Birth of the Idea of Photography Cite Icon Cite Permissions Share Icon Share Twitter LinkedIn Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Stephen Petersen; The Birth of the Idea of Photography. Leonardo 2021; 54 (3): 357–359. doi: https://doi.org/10.1162/leon_r_02039 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll JournalsLeonardo Search Advanced Search This content is only available as a PDF. ©2021 ISAST2021ISAST Article PDF first page preview Close Modal You do not currently have access to this content.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.006
Scholarly communication0.0100.007
Open science0.0010.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0630.025

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 head0.222
Teacher spread0.204 · 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 designTheoretical or conceptual
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

Citations18
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueLeonardoSame topicPhotography and Visual CultureFrench-language works237,207