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Record W2015575205 · doi:10.5558/tfc77619-4

Ice damage impacts on the health of the northern New York State forest

2001· article· en· W2015575205 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Forestry Chronicle · 2001
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsnot available
FundersU.S. Forest ServiceNew York State Department of Environmental ConservationU.S. Department of Agriculture
KeywordsForest healthForest structureForestryBasal areaGeographyNational forestCrown (dentistry)Environmental scienceEcologyPhysical geographyBiologyMedicineCanopy

Abstract

fetched live from OpenAlex

Detailed crown condition information, including numbers of broken branches ≥ 5 cm diameter, broken tops, and healthy branches, were recorded for 5434 living trees > 9 cm dbh from 603 ten-basal-area-factor prism plots (three per forest stand) at 201 random points (stands) throughout the ice damage region of northern New York State. Twenty five percent of the sample stands had ≥ 20% branch breakage. Bigtooth aspen, red oak, red maple, and white pine had the most breakage. Comparison of potential mortality of trees associated with ≥ 75% ice damage (severe damage) to baseline (predicted) mortality to maintain the existing forest structure suggests that ice damage may alter the health of 18% of the forest stands but this is not sufficient to alter the health (sustainability) of the larger forest system. Key words: ice storm, forest health, sustainability, growth, mortality, dbh classes

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.292
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.240
Teacher spread0.216 · 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