MétaCan
Menu
Back to cohort
Record W2548062750

Saving Our Sugar Maples: Searching for Tough Survivors to Clone

2008· article· en· W2548062750 on OpenAlexfundaboutno aff
Adam Dale, Peter G. Kevan, Anne‐Marie Roussy

Bibliographic record

VenueThe Atrium (University of Guelph) · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaTree Research and Education Endowment Fund
Keywordsclone (Java method)SugarBiologyFood scienceGeneticsGene
DOInot available

Abstract

fetched live from OpenAlex

Have you noticed the poor condition of sugar maples in towns and cities and along Ontario’s roadsides? Many have dead limbs. For some, half the tree is gone. Why? You may hear some saying they are simply old trees that have lived their best days. Well, the truth is that most roadside sugar maples are only about 80 to 90 years-old, which isn’t old for this species. Healthy sugar maples can live 300, some say even 500 years.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0380.008

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 head0.025
GPT teacher head0.232
Teacher spread0.207 · 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 designBench or experimental
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

Citations2
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueThe Atrium (University of Guelph)Same topicForest Management and PolicyFrench-language works237,207