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Record W2021504013 · doi:10.1177/0309133312457107

Biogeosciences survey

2012· article· en· W2021504013 on OpenAlexaff
Y. E. Martin, Edward A. Johnson

Bibliographic record

VenueProgress in Physical Geography Earth and Environment · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversity of Calgary
FundersNational Science Foundation
KeywordsHydrosphereScope (computer science)Multidisciplinary approachHeading (navigation)Field (mathematics)Liquid waterData scienceEarth scienceComputer scienceManagement scienceBiosphereEcologySociologyEngineeringGeologySocial scienceAerospace engineering

Abstract

fetched live from OpenAlex

The biogeosciences are a rapidly expanding field, and for this reason the full scope of possible topics falling under this heading is not always recognized. The biogeosciences cover all fields of the biological sciences and their interactions with the relevant Earth spheres (i.e. atmosphere, hydrosphere, lithosphere), and are studied over a wide range of temporal and spatial scales. While interdisciplinary work has been recognized for many years, it is recommended that all biogeosciences studies should ultimately strive to understand process operation and feedbacks, and in doing so a common ground to approaches of study can be defined. The notion of multidisciplinary versus interdisciplinary research is considered herein. It is by following an approach of explanation-based science that the complex interplay of biological and environmental processes can be understood best. Understanding of system behaviour and functioning should be a core goal of biogeosciences research. This review offers a proposed classification and summary of the full range of topics falling under the umbrella of the biogeosciences, and in doing so sets the stage for a future series of progress reports focusing on recent developments in the biogeosciences.

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.091
Threshold uncertainty score0.306

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0150.033
Science and technology studies0.0010.000
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0910.067

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 head0.231
Teacher spread0.219 · 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

Citations39
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueProgress in Physical Geography Earth and EnvironmentSame topicMicrobial Community Ecology and PhysiologyFrench-language works237,207