MétaCan
Menu
← Back to cohort
Record W7128615491 · doi:10.15468/t9t3gd

University of Toronto: The Estuary of the Saint John River (1934-35)

2019· dataset· en· W7128615491 on OpenAlexaffabout
Harold M. Rogers, Mary Kennedy

Bibliographic record

VenueOpen MIND · 2019
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEstuarySAINTBayFlora (microbiology)Fish <Actinopterygii>Historical record

Abstract

fetched live from OpenAlex

In 1936 Harold M. Rogers published his university thesis 'The Estuary of the Saint John River'. This document is not accessible online but a pdf version may be obtained by contacting the University of Toronto directly. In his thesis Rogers states that observations were primarily restricted to the lower part of the estuary with the majority of the sampling taking place on Kennebecasis Bay and Long Beach. His thesis is divided into three parts: physiography; study of the flora and fauna; and the fish and fisheries. This resource contains species occurrence records extracted from the thesis text. This version of the dataset includes simple species occurrence records for the area of the estuary. The thesis (Rogers 1936) contains detailed descriptions of the various taxa.

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)0.004
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 score0.634
Threshold uncertainty score0.728

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.013
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0660.080

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 head0.031
GPT teacher head0.279
Teacher spread0.248 · 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
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueOpen MIND→French-language works237,207→