MétaCan
Menu
Back to cohort
Record W2091523684 · doi:10.1139/x03-011

Combined effects of site preparation, soil properties, and sowing date on the establishment of <i>Pinus sylvestris</i> and <i>Picea abies</i> from seeds

2003· article· en· W2091523684 on OpenAlexvenueno aff
Michelle de Chantal, Kari Leinonen, Hannu Ilvesniemi, Carl Johan Westman

Bibliographic record

VenueCanadian Journal of Forest Research · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsnot available
Fundersnot available
KeywordsPicea abiesScots pineGrowing seasonSeedlingWater contentSowingPinus <genus>Environmental scienceAgronomyDesiccationFrost (temperature)MoistureSoil horizonSoil waterHorticultureBotanyBiologyGeologyGeographySoil science

Abstract

fetched live from OpenAlex

The aim of this study is to determine the effect of site preparation on soil properties and, in turn, the emergence, mortality, and establishment of Pinus sylvestris L. (Scots pine) and Picea abies (L.) Karst. (Norway spruce) seedlings sown in spring and summer along a slope with variation in soil texture and moisture. Three site preparation treatments of varying intensities were studied: exposed C horizon, mound (broken L–F–H–Ae–B horizons piled over undisturbed ground), and exposed Ae–B horizons. Seedling emergence was higher in the moist growing season than in the dry one. During a dry growing season, mounds and exposed C horizon had negative effects on soil moisture that increased mortality. Moreover, frost heaving was an important cause of winter mortality on mounds and exposed C horizon, whereas frost heaving was low on exposed Ae–B horizons, even though soil moisture and the content of fine soil particles (&lt;0.06 mm) were high. Frost heaving mortality was higher for summer-sown than for spring-sown seedlings and for P. abies than for P. sylvestris. Growing season mortality was high following a winter with frost heaving, suggesting that roots were damaged, thereby making seedlings more susceptible to desiccation.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.056
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.030
GPT teacher head0.241
Teacher spread0.212 · 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 teacher head, 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

Citations46
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicSeedling growth and survival studiesFrench-language works237,207