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Record W7128801978 · doi:10.15468/hkw8rn

FRB: Bottom fauna of Saint John Harbour and estuary as surveyed in 1959 and 1961

2021· dataset· en· W7128801978 on OpenAlexaffabout
Delphine C. Maclellan, J .B. Sprague

Bibliographic record

VenueOpen MIND · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsGovernment of Canada
Fundersnot available
KeywordsHarbourFaunaBaySAINTEstuaryRefineryEcosystemTransect

Abstract

fetched live from OpenAlex

Two surveys to collect bottom fauna in the harbour and estuary at Saint John, New Brunswick were conducted in 1959 and 1961. The objective was to see if there were changes caused by pollution from an oil refinery - the Irving Oil Refinery in East Saint John released most of its chemical wastes into Saint John Harbour through a pipeline terminating near the tip of Courtenay Bay breakwater (near survey station X). The refinery started up in stages from late March to mid-June 1960 by which time it was in full operation. Species distribution information associated with this study were digitized, standardized and republished as part of the Atlantic Coastal Zone Information Steering Committee (ACZISC) Atlantic Ecosystem Initiative (AEI) funded project “Atlantic Canada’s Biological Data for Ecosystem Planning and Decision-making” and OBIS Canada.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.385
Threshold uncertainty score0.774

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.020

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 head0.035
GPT teacher head0.323
Teacher spread0.287 · 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 designObservational
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 routes2
Has abstractyes

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