MétaCan
Menu
← Back to cohort
Record W4393537858 · doi:10.5281/zenodo.10227180

Oak Island, Nova Scotia, Canada

2021· dataset· en· W4393537858 on OpenAlexaboutno aff
arizonaguide

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaNova (rocket)GeographyOceanographyGeologyArchaeologyEngineeringAeronautics

Abstract

fetched live from OpenAlex

3D image of Oak Island, Nova Scotia, Canada Oak Island is a 57-hectare (140-acre) privately owned island in Lunenburg County on the south shore of Nova Scotia, Canada. The tree-covered island is one of about 360 small islands in Mahone Bay and rises to a maximum of 11 metres (36 feet) above sea level. The island is located 200 metres (660 feet) from shore and connected to the mainland by a causeway and gate. The nearest community is the rural community of Western Shore which faces the island, while the nearest village is Chester. The island is best known for various theories about possible buried treasure or historical artifacts, and the associated exploration. https://en.wikipedia.org/wiki/Oak_Island Source: Objaverse 1.0 / Sketchfab

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)0.000
metaresearch head score (Gemma)0.002
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.101
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.007
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0630.072

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 head0.201
Teacher spread0.180 · 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
GenreDataset

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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicMarine and coastal plant biology→French-language works237,207→