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Record W7100384324

RESt ~ OF THE ECOLOG!CAL ASPECTS OF rHE VEGETATIVE TYPES ON LATOUR STATE FOREST

2013· article· en· W7100384324 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSnowSnow coverPrecipitationFalling (accident)State (computer science)Plant lifeRest (music)
DOInot available

Abstract

fetched live from OpenAlex

Some o ~ the broad characteristics of the four prominant vegetative cover types as found on Latour and elsewhere in this state are described below. NIXED CONIFER STANDS This complex is common to the timber lands of California. These stands may be _ seen in the Sierra Nevada, Cascade dnd Coast Ranges. As with all coniferous species, trees forming these stands are found on increasingly higher elevations at lower latitudes. In Northern California they occur at elevations from 2000 feet to about 5000 feet. Merriam identifies this as a Transition Life Zone, one between the Upper Sonoran of the Central Valley and the Canadian, as found near the upper reaches of these mountain ranges. Cold wet winters with hot dry summers are common in these stands, especially in this State. Average minimum temperatures will reach-25 degrees F., while maximum temperatures will often exceed 100 degrees F. Annual precipitation may vary from 20 to 90 inches, much of it falling as snow during January and February. Though a mixed stand may vary in species composition, depending on its geographical location, in the western states the usual combination of species in a mixed conifer stand is:

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.024
GPT teacher head0.210
Teacher spread0.186 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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