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Record W7081916412 · doi:10.52230/ndmr7949

'Introduction'

2025· article· en· W7081916412 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Australian Canadian and Aotearoa New Zealand Studies · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsAotearoaScope (computer science)PublicationIndigenousMultidisciplinary approach

Abstract

fetched live from OpenAlex

The aim and scope of the Journal of Australian, Canadian, and Aotearoa New Zealand Studies (JACANZS) is to publish articles in various disciplines (history, politics, literature, law, anthropology, and Indigenous studies) on one or more of the following countries: Australia, Canada, and Aotearoa New Zealand, with a core on articles that are comparative in their geographic remit, for example Australia and Aotearoa New Zealand, or Australia and Canada. The creation of the journal responds to a lack of journals that collectively publish across the fields of Australian, Canadian, and Aotearoa New Zealand Studies from inter- and multidisciplinary perspectives. It also followed the creation of the Australian, Canadian, and New Zealand Studies Network (ACNZSN) to reflect the work and membership of the network.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.699
Threshold uncertainty score0.997

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0060.004
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.3010.157

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 head0.021
GPT teacher head0.261
Teacher spread0.240 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2025
Admission routes1
Has abstractyes

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