MétaCan
Menu
Back to cohort
Record W2981365683 · doi:10.4095/296957

MAXIMA: software to determine local maxima from gridded data

2015· report· en· W2981365683 on OpenAlexaff
R Dumont, Z Bardossy, W Miles

Bibliographic record

Venuenot available
Typereport
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsMaximaSoftwareMaxima and minimaEnvironmental scienceComputer scienceGeologyMathematicsOperating systemHistoryMathematical analysis

Abstract

fetched live from OpenAlex

MAXIMA is a Geosoft GX implementation of a method of identifying local maxima from gridded data described by Blakely and Simpson (1986). The routine determines local maxima in 1, 2, 3, or 4 directions. The position of the local maximum value is calculated from 9 local grid cells and is an improvement on methods using grid cell centres as the position of the maxima. Local maxima can be discriminated by a user supplied minimum input grid value. The output maxima are written to a Geosoft GDB file.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.281
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0050.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.004

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 head0.590
GPT teacher head0.510
Teacher spread0.080 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreMethods

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
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicSimulation Techniques and ApplicationsFrench-language works237,207