MétaCan
Menu
← Back to cohort
Record W3136089639

Microbial Diversity and Biogeochemistry of a Shallow Pristine Canadian Shield Groundwater System

2012· article· en· W3136089639 on OpenAlexaffabout
V. Shirokova, Grant Ferris

Bibliographic record

VenueAGU Fall Meeting Abstracts · 2012
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiogeochemistryGroundwaterAcidobacteriaFirmicutesEnvironmental chemistryWeatheringActinobacteriaPhotic zoneGeologySurface waterWater tableEnvironmental scienceHydrology (agriculture)EcologyMineralogyChemistryGeochemistryBiologyPaleontologyEnvironmental engineeringBacteriaNutrient
DOInot available

Abstract

fetched live from OpenAlex

An investigation was conducted to assess the microbial diversity and biogeochemistry of a pristine shallow glaciofluvial groundwater system on the Canadian Shield. Vadose zone sands were very fine-grained, consisting mostly of iron oxide-coated quartz. Below the water table in the saturated zone, iron oxide-coating on quartz grains were absent, owing presumably to reductive dissolution by Fe(III)-reducing bacteria and chemical weathering, respectively. Groundwater pH was circumneutral at 6.4 + 0.1, and Eh was slightly reducing at 349 ± 15 mV compared to local surface waters at 417 ± 21 mV; the total dissolved solids concentration in groundwater was 45.2 ± 6.9 mg/L. A total of 269 clones were sequenced and compiled into a 16S rRNA gene library, and representative operational taxonomic units (OTU) were retrieved from basic local alignment search tool (BLAST) analyses at the species-level across 7 phyla, including Acidobacteria, Actinobacteria, Bacteroidetes, Chlorobi, Firmicutes, Planctomycetes, and Proteob...

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.072
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.188
Teacher spread0.176 · 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 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
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueAGU Fall Meeting Abstracts→Same topicHydrocarbon exploration and reservoir analysis→French-language works237,207→