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Record W1485350351 · doi:10.5821/iwp.2009.7.15755

Advancing the interoperability of ocean sensors. Workshop demostration at ocean innovation 2008 congress.

2009· article· en· W1485350351 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInstrumentation viewpoint · 2009
Typearticle
Languageen
FieldComputer Science
TopicSensor Technology and Measurement Systems
Canadian institutionsnot available
Fundersnot available
KeywordsInteroperabilityGeospatial analysisSensor webComputer scienceWireless sensor networkSystems engineeringTelecommunicationsWorld Wide WebEngineeringComputer networkRemote sensingGeographyKey distribution in wireless sensor networks

Abstract

fetched live from OpenAlex

The aim of this project is to implement a smart sensor worldwide network based on IEEE 1451 family of standards which can provide multiple interoperable clients to access geospatial and sensor data for national local monitoring.This paper presents part of an integrated ocean observing system (IOOS)developed by SARTI research group which offers remotely access via the Web to sensors and sensor networks in Canada, USA and Europe.It also describes the capabilities and functions of such a network and possibilities to access multiple sensor observation and sensors via OGC SWE and IEEE 1451.The architecture of sensor network is based on the IEEE 1451.0.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.276
Teacher spread0.249 · 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