Microbial activity and carbon fluxes in rainforest soil – Tsunami Hill, Calvert Island – June 2015 - April 2016
Bibliographic record
Abstract
This dataset is designed to elucidate the microbial drivers of carbon fluxes from deep ombrotrophic peat bog and bog forest ecosystem comparison plots (ECP) on Calvert Island as part of the Kwakshua Watersheds Program (KWP). This dataset was collected between June 2015 and April 2016 at the Tsunami Hill ECP sites. It combines: -Soil chemistry (total carbon, total nitrogen, NH4-N, NO3N, total sulphur, available PO4-P, pH, cations) -Micrometeorology (precipitation, air temperature, soil temperature, soil redox potential, soil gravimetric water content, water table depth) -Soil water chemistry (dissolved organic carbon (DOC), specific absorbance of DOC at 254nm (SUVA254), cations), -Soil gas flux measurements (CO2, CH4, N2O), -Fungal ITS, Eukaryotic ribosomal small-subunit (SSU) amplicon sequences from DNA and RNA, prokaryotic SSU amplicon sequences from DNA and RNA -Metatranscriptomes Detailed information regarding field names and descriptions are available with the dataset through the link below. Basic methods are outlined in the supplemental information section of this record and detailed methods are available in the associated publication (Levy-Booth et al. 2018) Cite as: Levy-Booth, D.J, I.J.W. Giesbrecht, C.T.E. Kellogg, T.J. Heger, D.V. D’Amore, P.J. Keeling, S.J. Hallam, W.W. Mohn (2018). Seasonal and ecohydrological regulation of active microbial populations involved in DOC, CO2 and CH4 fluxes in temperate rainforest soil. Version 1.0. Hakai Institute. Dataset. doi: 10.21966/1.715630. [access date]. DOI: 10.21966/1.715630
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".