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Record W4224070652 · doi:10.1101/2022.04.13.487781

Spinosaurids as ‘subaqueous foragers’ undermined by selective sampling and problematic statistical inference

2022· preprint· en· W4224070652 on OpenAlexaff
Nathan Myhrvold, Paul C. Sereno, Stephanie L. Baumgart, Kiersten K. Formoso, Daniel Vidal, Frank E. Fish, Donald M. Henderson

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsRoyal Tyrrell Museum
Fundersnot available
KeywordsInferenceSampling (signal processing)TaxonPaleontologyGeologyTrunkUnderwaterComputed tomographicGeographyBiologyEcologyComputed tomographyArchaeologyComputer scienceArtificial intelligenceComputer visionRadiologyMedicine

Abstract

fetched live from OpenAlex

Abstract Fabbri et al. 1 claim that the huge sail-backed dinosaur Spinosaurus aegyptiacus and the spinosaurid Baryonyx were “subaqueous foragers,” diving underwater in pursuit of prey, based on their measure of bone “compactness.” Using thin-sections and computed tomographic (CT) scans of thigh bone (femur) and trunk rib from various living and extinct vertebrates, they claim to be able to distinguish taxa with “aquatic habits” from others. Their conclusions are undermined by selective bone sampling, inaccuracies concerning spinosaurid bone structure, faulty statistical inferences, and novel redefinition of the term “aquatic.”

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)0.040
metaresearch head score (Gemma)0.093
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.093
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.006
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0020.002
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 head0.017
GPT teacher head0.238
Teacher spread0.221 · 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.

Study designTheoretical or conceptual
DomainMethods
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

Citations9
Published2022
Admission routes1
Has abstractyes

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