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Record W4253151299 · doi:10.14351/0831-4985-28.1.63

Networking nature: Building cybercabinets of digital curiosities

2014· article· en· W4253151299 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCollection Forum · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsWorld Wide WebThe InternetNatural (archaeology)Computer scienceNatural historyHistory

Abstract

fetched live from OpenAlex

In the age of the Internet, engaging the public online is critical to building audiences and broadening support for natural history. While collections managers have been providing online access to collections through sophisticated database search interfaces, less progress has been made to present these resources in a user-friendly framework. Some museums are thinking in terms of networked online knowledge and radically shifting the way they broker their digital content. This research examines ways natural history can be effectively presented online to the public by reviewing relevant literature, analyzing six model sites with a heuristic evaluation tool and a user survey, and exploring three case studies through project personnel interviews. Findings summarize important strategies for cultivating creative online access to natural history digital resources and culminate in offering guidelines for building these “cybercabinets” of digital natural history specimens.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.828
Threshold uncertainty score0.368

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 studies0.0000.000
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 head0.012
GPT teacher head0.212
Teacher spread0.200 · 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