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Record W6948035959 · doi:10.5066/f7t43r7t

Marine magnetic data from twelve cruises of Pioneer and Rehoboth in 1955 and 1956 off British Columbia, Washington, Oregon, and California

2023· dataset· en· W6948035959 on OpenAlexaboutno aff

Bibliographic record

VenueUSGS DOI Tool Production Environment · 2023
Typedataset
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsCruiseEarth's magnetic fieldRaw dataData setNautical mile

Abstract

fetched live from OpenAlex

This shapefile contains total?field marine magnetic data from eleven cruises of the USCGS ship Pioneer (OSS?31) and one cruise from the USS Rehoboth (AGS?50) in deep water off the west coast of the United States and southern British Columbia in 1955 and 1956. Magnetic anomalies are calculated with the latest definitive geomagnetic reference field (DGRF) included in the 12th Generation of the International Geomagnetic Reference Field model (Th�bault and others, 2015). The marine magnetic data from these cruises were recovered from backup tapes that archived the work of Skaer and Hey in the late 1980s (Skaer, 1989). Fernandez and Hey (1991) merged these 1950s data with magnetic data from subsequent cruises. Raw data are provided in individual?cruise CSV files and industry standard MGD77T files, which are also available in the data release. Our recovery of the 1991 data from legacy media provides a data set that helps advance magnetic field studies in the region.

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 score0.503
Threshold uncertainty score0.989

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.008
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0270.019

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 head0.217
Teacher spread0.196 · 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
Published2023
Admission routes1
Has abstractyes

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Same venueUSGS DOI Tool Production EnvironmentSame topicSpecies Distribution and Climate ChangeFrench-language works237,207