MétaCan
Menu
← Back to cohort
Record W2594748282 · doi:10.5194/bg-14-5115-2017

Reviews and syntheses: on the roles trees play in building and plumbing the critical zone

2017· article· en· W2594748282 on OpenAlexaff
Susan L. Brantley, David M. Eissenstat, Jill Marshall, Sarah E. Godsey, Zsuzsanna Balogh‐Brunstad, D. L. Karwan, S. A. Papuga, Joshua J. Roering, Todd E. Dawson, Jaivime Evaristo, Oliver A. Chadwick, Jeffrey J. McDonnell, Kathleen C. Weathers

Bibliographic record

VenueBiogeosciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Saskatchewan
FundersNational Science Foundation
KeywordsBiogeochemical cycleSubstrate (aquarium)Environmental scienceTree (set theory)Earth sciencePhosphorusSoil scienceGeologyEcologyBiologyChemistryMathematics

Abstract

fetched live from OpenAlex

Abstract. Trees, the most successful biological power plants on earth, build and plumb the critical zone (CZ) in ways that we do not yet understand. To encourage exploration of the character and implications of interactions between trees and soil in the CZ, we propose nine hypotheses that can be tested at diverse settings. Depending upon one's disciplinary background, many of the hypotheses may appear obviously true or obviously false. We infer from this lack of agreement that the following nine hypotheses are important and must be tested to advance critical zone science. (1) Tree roots can only physically penetrate and biogeochemically comminute the immobile substrate underlying mobile soil when that underlying substrate is fractured or pre-weathered. (2) In settings where the depth of weathered material, H, is large, trees primarily shape the CZ through biogeochemical reactions within the rooting zone. (3) In forested uplands, the thickness of mobile soil, h, can evolve toward a steady state because of feedbacks related to root disruption and tree throw. (4) In settings where h

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)0.004
metaresearch head score (Gemma)0.026
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0120.022
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0170.005

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 head0.026
GPT teacher head0.261
Teacher spread0.236 · 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
GenreReview

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

Citations217
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueBiogeosciences→Same topicPlant Water Relations and Carbon Dynamics→French-language works237,207→