MétaCan
Menu
Back to cohort
Record W2588999683 · doi:10.1093/jicru_1.2.7

Quantities, Units and Terms in Radioecology: Abstract

2001· article· en· W2588999683 on OpenAlexaff
F. W. Whicker, K. Bunzl, Philip M. Dixon, Mary T. Scott, Steve Sheppard, G. Voigt

Bibliographic record

VenueJournal of the ICRU · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsRadioecologyGlossaryScope (computer science)ConfusionHarmonizationSection (typography)Field (mathematics)Set (abstract data type)Environmental scienceComputer scienceMathematicsPsychologyRadionuclidePhysicsPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Abstract This report provides the first comprehensive and authoritative set of definitions for quantities, units and terms used in the highly interdisciplinary field of radioecology. The scope of this report is the presentation of the primary quantities and terms that are used in studies of radionuclide transport in the environment and those used to help assess the effects of environmental radioactivity on plants, animals and humans. The first section of the report defines the quantities frequently used in radioecology. Explanatory comments are provided, and special conditions that must be specified for the quantities to be fully understood are given. To encourage greater uniformity and to minimise confusion in this field, both the currently recommended and previously used names and symbols are given. The second section provides a glossary of scientific terms that are often used in radioecology. Many of these terms are common to one or more other scientific disciplines that have been applied to radioecology studies. A number of appendices are also included which provide common and scientific names of selected plant and animal species that are commonly studied in radioecology.

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)0.006
metaresearch head score (Gemma)0.018
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.016
Science and technology studies0.0020.007
Scholarly communication0.0080.008
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.009

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 head0.015
GPT teacher head0.224
Teacher spread0.210 · 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
GenreMethods

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

Citations5
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the ICRUSame topicRadioactive contamination and transferFrench-language works237,207