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Record W6929593073 · doi:10.5061/dryad.fv322/1

Sample tree growth data with locations

2017· other· en· W6929593073 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2017
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsPinus contortaPicea engelmanniiSample (material)Geodetic datumAbies lasiocarpaElevation (ballistics)Site indexDendrochronologyTree (set theory)

Abstract

fetched live from OpenAlex

This file provides measurements of annual radial growth for randomly distributed adult trees in the Rocky Mountains of the United States. Measurements were derived from increment cores collected in 2012 and 2013. A total of 5 tree species were sampled. Sample trees were distributed across a latitudinal gradient from the southern terminus of the Rockies in New Mexico to the Canadian border in the north. Target tree species include: Abies lasiocarpa (subalpine fir), Picea engelmannii (Engelmann spruce), Pinus contorta (lodgepole pine), Pinus ponderosa (ponderosa pine) and Pseudotsuga menziesii (Douglas-fir). Annual radial increment over a 20 year period was measured in millimeters for each sample tree. File headings include:\n\nSample tree ID: Identification code for the sample or target tree\nSpecies: Species of the sample tree\nYear: The year of growth\nSite: General location of sample tree\nLongitude and Latitude: Geographical coordinates of sample (based on North American Datum 1983)\nElevation: Elevation above sea level in meters\nAspect: Dominant terrain aspect in degrees from north\nTerrain slope: Average slope of land surface measured in percent\nStem diameter: Diameter of tree stem at breast height (1.3 meters above root crown) in year of growth measured in centimeters\nAge: Age of sample in year of growth\nRing width: Measured width of annual radial increment in millimeters\nDate collected: Month, day, and year the sample was collected

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Other · Consensus signal: none
Teacher disagreement score0.568
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1360.008

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 head0.100
GPT teacher head0.292
Teacher spread0.192 · 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
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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