MétaCan
Menu
← Back to cohort
Record W6950401773 · doi:10.5683/sp3/lfnpeq

Killer Whale 3D Model

2024· dataset· en· W6950401773 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2024
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsFisheries and Oceans CanadaNational Research Council CanadaMcGill University
Fundersnot available
KeywordsWhaleMobile deviceEvent (particle physics)LidarPregnancy

Abstract

fetched live from OpenAlex

On March 23, 2024, a handheld LiDAR device (iPhone running Scaniverse) was used to collect 3D scans on a 6.02-meter pregnant adult female Killer Whale (Orcinus orca) and her unborn fetus. These scans were conducted during a live stranding event near Zeballos, B.C., Canada, where the adult female and calf became trapped in a lagoon. Despite efforts to return the adult to the water, she sadly died later in the day. The handheld LiDAR allowed us to capture highly detailed and accurate morphological data of both the adult female and the unborn fetus before the necropsy commenced.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.041
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0340.051

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 head0.013
GPT teacher head0.218
Teacher spread0.206 · 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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueBorealis→Same topicOceanographic and Atmospheric Processes→French-language works237,207→