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Record W2518047913 · doi:10.1186/s40152-016-0052-2

Ocean tracking technologies: observing species at risk

2016· article· en· W2518047913 on OpenAlex
Richard Apostle, Tsafrir Gazit

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

VenueMAST. Maritime studies/Maritime studies · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsTracking (education)PoliticsEndangered speciesFish <Actinopterygii>Term (time)Environmental resource managementComputer scienceEnvironmental planningPolitical scienceFisheryGeographyEnvironmental scienceEcologySociologyBiologyLaw

Abstract

fetched live from OpenAlex

The Ocean Tracking Network is a major global project to establish tracking of endangered fish and marine mammal species through acoustic telemetry. The project has only begun to generate the policy-related outcomes that may be utilized as benchmarks for evaluating the success of the project. We propose that projects like this one make technical advances before scientific ones, and that scientific advances may be quite long term. Further, the development of policy outcomes is shaped by the larger political economies in which the technologies are located; scientists are quite used to “flying under the radar”, waiting for more propitious circumstances. There are serious questions regarding which actors are capable of making matters of fact issues of public debate.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.725
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.004
Scholarly communication0.0000.001
Open science0.0010.011
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.052
GPT teacher head0.282
Teacher spread0.230 · 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