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Record W1909730480 · doi:10.7717/peerj.1168

Non-repeatable science: assessing the frequency of voucher specimen deposition reveals that most arthropod research cannot be verified

2015· article· en· W1909730480 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePeerJ · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsMcGill University
Fundersnot available
KeywordsVoucherDeposition (geology)Computer scienceData scienceBiologyWorld Wide Web

Abstract

fetched live from OpenAlex

Scientific findings need to be verifiable and grounded in repeatability. With specimen-level research this is in part achieved with the deposition of voucher specimens. These are labeled, curated, data-based specimens that have been deposited in a collection or museum, available for verification of the work and to ensure researchers are calling the same taxa by the same names. Voucher specimens themselves are the subject of research, from the discovery of new species by taxonomists to ecologists documenting historical records of invasive species. Our objective was to quantify the frequency of voucher specimen deposition in biodiversity and community ecology research through a survey of the peer-reviewed literature about arthropods, from 1989 until 2014. Overall rates of voucher deposition were alarmingly low, at under 25%. This rate increased significantly over time, with 35% of papers reporting on vouchers in 2014. Relative to the global mean, entomological research had a significantly higher rate of voucher deposition (46%), whereas researchers studying crustaceans deposited vouchers less than 6% of the time, significantly less than the mean. Researchers working in museums had a significantly higher frequency of voucher deposition. Our results suggest a significant culture shift about the process of vouchering specimens is required. There must be more education and mentoring about voucher specimens within laboratories and across different fields of study. Principal investigators and granting agencies need a proactive approach to ensuring specimen-level data are properly, long-term curated. Editorial boards and journals can also adopt policies to ensure papers are published only if explicit statements about the deposition of voucher specimens is provided. Although the gap is significant, achieving a higher rate of voucher specimen deposition is a worthy goal to ensure all research efforts are preserved for future generations.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.167
GPT teacher head0.385
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