MétaCan
Menu
Back to cohort
Record W1499112679

Paleoecology of the Bolivian Pantanal: A 45,000 year history of vegetation and climate change in tropical South America

2009· dissertation· en· W1499112679 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueERA · 2009
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersNatural Environment Research CouncilNatural Sciences and Engineering Research Council of CanadaAberystwyth UniversityGovernment of the United KingdomNational Geographic Society
KeywordsPaleoecologyClimate changeVegetation (pathology)GeographyTropicsPhysical geographyAgroforestryEcologyEnvironmental scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

This thesis is formatted in journal style, and as is typical of research submitted to peer-reviewed journals, some of the data included in the three research chapters have been collected by collaborating authors. These authors are listed at the beginning of each chapter, and the contribution of each is detailed below. Chapter 2 incorporates a vegetation survey around the shores of the field site, Laguna La Gaiba, conducted by Ezequiel Chavez and René Guillén of the Muséo de Historía Natural Noel Kempff Mercado, Santa Cruz, Bolivia, and Michael J. Burn differentiated the pollen of Moraceae and Urticaceae in twenty-five horizons. Toby Pennington of the Royal Botanic Gardens, Edinburgh, has been crucial to data interpretation and discussion. The research in Chapter 3 also relies on the field surveys of Ezequiel Chavez and René Guillén, as well as the finer-scale pollen differentiation provided by Michael J. Burn. This chapter also includes carbon isotope data obtained by Neil J. Loader and Alayne Street-Perrott, Swansea University, Wales, and elemental data collected by Francis E. Mayle and Michael H. Marshall (Aberystwyth) at the Itrax XRF scanner facility, University of Aberystwyth. As in the preceding chapter, Toby Pennington has played an integral role in the ecological interpretation and climatic significance of changes in the inundation-tolerant forest. The data obtained for Chapter 4 were collected entirely by my own hand, but the interpretation of these data was improved by contributed work of my co-authors in the previous two chapters.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.016
GPT teacher head0.246
Teacher spread0.229 · 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