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Record W2122224298 · doi:10.1029/2003gl017892

Limestones distinguished by magnetic hysteresis in three‐dimensional projections

2003· article· en· W2122224298 on OpenAlexafffund
Graham J. Borradaile, Tom Hamilton

Bibliographic record

VenueGeophysical Research Letters · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGeomagnetism and Paleomagnetism Studies
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of CanadaLakehead University
KeywordsHysteresisGeologyProjection (relational algebra)PaleomagnetismMagnetic hysteresisPlane (geometry)Space (punctuation)Orientation (vector space)Rock magnetismMagnetiteGeometrySedimentary depositional environmentRemanenceMineralogyPhysicsPaleontologyMathematicsMagnetizationCondensed matter physicsMagnetic fieldComputer science

Abstract

fetched live from OpenAlex

Magnetic hysteresis data determine the suitability of rocks for paleomagnetic work, provide clues to paleo‐environment and paleo‐climate and they may characterize depositional environments for limestones. However, the variables chosen for conventional two‐dimensional hysteresis plots, such as that of Day et al. [1977] , are not always suitable to discriminate between samples. Distinguishing samples by their regression surfaces in 3D hysteresis space may be more successful in some cases [ Borradaile and Lagroix, 2000 ] but a 2D projection with a less arbitrary viewing axis is preferable for routine reporting. We show that limestone samples are simply discriminated in a new 2D projection produced by projecting hysteresis data from three dimensions (x, y, z = Mr/Ms, Bcr, Bc) onto a plane containing the Mr/Ms axis. The orientation of the plane is controlled by its x‐axis that is defined by a suitably selected Bcr/Bc ratio, most often in the magnetite PSD range, 2< (Bcr/Bc) < 4.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.293
Teacher spread0.270 · 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
GenreEmpirical

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

Citations9
Published2003
Admission routes2
Has abstractyes

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