MétaCan
Menu
Back to cohort
Record W6892084876 · doi:10.5061/dryad.4qq6v/1

Biodiversity and Forest Structure at George Lake PSP

2017· other· en· W6892084876 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2017
Typeother
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsnot available
Fundersnot available
KeywordsBasal areaUnderstoryBiodiversityForest structureVegetation (pathology)Sampling (signal processing)Species richness

Abstract

fetched live from OpenAlex

Data from a permanent sampling plot (PSP) in central Alberta (Canada). All live and dead stems with DBH > 1.0 cm were identified and mapped within a 1 Ha (100m x 100m) plot. The plot was subdivided into 25 non-overlapping subplots (20m x 20m) and stem data summarized at this level. In addition, from each of these 25 subplots, biodiversity data (ground-dwelling spiders and carabid beetles, foliage-dwelling spiders, and understory vascular plants) were collected. The data consists of six spreadsheets. The first sheet contains univariate summaries of forest structure for each subplot (live and dead stem density and basal area, and in three DBH classes: DBH1: 1.0-4.9 cm; DBH2: 5-20 cm; DBH3: > 20 cm). The second sheed contains multivariate summaries of forest structure for each subplot (live and dead stem density and basal area by species). The remaining sheets contain raw abundances (ground-dwelling spiders and carabid beetles, and foliage-dwelling spiders) or percent cover (understory vascular plants) for species collected and/or observed in each of the 25 subplots.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.011
GPT teacher head0.186
Teacher spread0.176 · 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
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

Explore more

Same venueFigshareSame topicSmart Grid Security and ResilienceFrench-language works237,207