MétaCan
Menu
Back to cohort
Record W4394275985 · doi:10.6084/m9.figshare.13114433

Concentration, 13C, and 14C of dissolved and ebullition methane, dissolved inorganic carbon, dissolved organic carbon, particulate organic carbon and ebullition CO2 in rivers and thermokarst lakes in Northern Quebec, Canada

2020· dataset· en· W4394275985 on OpenAlexaboutno aff
Regina Gonzalez Moguel, Peter Douglas, Mark H. Garnett, Adrian M. Bass, Benjamin Keenan, Alex Matveev, Martin Pilote

Bibliographic record

VenueFigshare · 2020
Typedataset
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsnot available
FundersNatural Environment Research Council
KeywordsDissolved organic carbonThermokarstEnvironmental chemistryMethaneTotal organic carbonEnvironmental scienceCarbon fibersParticulatesPermafrostGeologyChemistryOceanographyMaterials science

Abstract

fetched live from OpenAlex

The dataset includes concentration, <sup>13</sup>C, and <sup>14</sup>C measurements of dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), particulate organic carbon (POC), total particulate carbon (TPC), sediment carbon and organic carbon, dissolved and ebullition methane (CH<sub>4</sub>), and ebullition carbon dioxide (CO<sub>2</sub>) from five lakes and three rivers in an area of sporadic permafrost degradation in Northern Quebec. <br><br>We sampled the three thaw lakes SAS2A, SAS2B, and SAS2C, located in a peatland adjacent to the Sasapimakwananisikw River (SAS2 peatland), in August 2018, August 2019, and February 2019. The other two lakes, KWK1 and KWK12, located in the once-glaciated KWK valley adjacent to the Kwakwatanikapistikw River, were sampled in August 2019 and 2019. <br><br>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.008
GPT teacher head0.184
Teacher spread0.177 · 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.

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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueFigshareSame topicSmart Materials for ConstructionFrench-language works237,207