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Record W4394389940 · doi:10.6084/m9.figshare.16807495

BIOL 3250 Birdwatching dataset.pdf

2021· dataset· en· W4394389940 on OpenAlexaboutno aff
Wi-Am Saad

Bibliographic record

VenueFigshare · 2021
Typedataset
Languageen
FieldComputer Science
TopicData Analysis with R
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The data collected from the birdwatching pilot examines additional behaviour of how species interact with each other in regards to aggression and territoriality. The dataset is presented in a table which contains 6 columns containing information on how data was compiled. The first column contains the repetitions which are the dates the experiment, birdwatching, took place. The second column kept track of the researcher who was conducting observation. Column three was the area in which data was being collected which was at a local creek by Elmcreek park in the city of Mississauga Ontario over the span of two days for a total of two and a half hours divided across both days. Column four was the common-name species observed and column five compiled the frequency in which that species participated in a particular behaviour not as an individual but as separate individuals. Column six was the behaviour the birds were observed doing from foraging to species interactions. Data was collected in the early morning between 10 am-12 pm on September 12th and 2 pm-3pm on September 13th. The initial day of sampling the temperature was sunny with slight clouding whereas it was cloudier on the second day with a little more wind.

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)0.001
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.133
Threshold uncertainty score0.445

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1330.174

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 head0.036
GPT teacher head0.284
Teacher spread0.247 · 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
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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