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BIOL3250 -- BIOBLITZ (DATA & METADATA FOR FIELD EXPERIMENT).xlsx

2022· dataset· en· W4394174006 on OpenAlexaboutno aff
Natela Wasilenco

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldComputer Science
TopicStatistical and Computational Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsMetadataField (mathematics)Computer scienceWorld Wide WebMathematics

Abstract

fetched live from OpenAlex

This study was conducted to compare the richness of the diversity of frogs in the woodlots (Hugh Bennett Woodlot & Thornhill Woods Woodlot 4) in ON, Canada near my house identified using iNaturalist app, record frogs' activity time, as well as compare the best suitable conditions for their activity while tracking weather changes using Apple Weather app. On the last day of my experiment there were no more frogs observed at any of the sites due to fall/wintertime hibernation. (Student number: 216621385; TA: Mario Zuliani)

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.426
Threshold uncertainty score0.818

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0040.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.4260.305

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 head0.242
GPT teacher head0.380
Teacher spread0.138 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2022
Admission routes1
Has abstractyes

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