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Record W7097999316

Third International Symposium on Deep-Sea Corals Science and Management

2005· article· en· W7097999316 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPleasureAdvisory committeeSociology of scientific knowledgeSpecial Interest Group
DOInot available

Abstract

fetched live from OpenAlex

It is a great pleasure to welcome you all to the 3 rd International Symposium on Deep-Sea Corals. The purpose of the symposium is to provide a forum for scientific information exchange and explore new concepts and future collaboration among the participants. What will be discussed over the course of the next few days promises to be an exciting insight into the significant advances in ocean science and management of coldwater corals, sponges, seamounts, and associated fauna. We hope that you will participate in the creative discussions that will expand our collective understanding of the complex array of topics under the eight themes developed by the symposium advisory committee. Increasing interest in understanding and protecting deep-water ecosystems is clearly evident in discussions taking place at the United Nations and in several countries around the world. Interest in presenting and discussing scientific advances and ways to protect these areas has grown as well. In 2000, the 1 st International Symposium on Deep-Sea Corals took place in Halifax, Canada, with 42 oral presentations and 22 posters comprising the agenda. Three years later in Erlangen, Germany, the symposium had grown into 67 oral presentations and 42 posters. Realizing that the amount of interest and scientific advances in deepwater ecology was quickly

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)0.002
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0450.012

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 head0.008
GPT teacher head0.223
Teacher spread0.214 · 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
GenreOther

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
Published2005
Admission routes1
Has abstractyes

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