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Record W1960317390 · doi:10.1016/0967-0653(95)91490-0

10.1016/0967-0653(95)91490-0

2000· article· en· W1960317390 on OpenAlexvenueno aff
Jacques Laborel, Françoise Laborel-Deguen

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyMediterranean climateMediterranean seaCoralline algaeReefSubmersion (mathematics)Sea levelTectonicsOceanographyElevation (ballistics)PaleontologySeismologyGeographyArchaeology

Abstract

fetched live from OpenAlex

During a study of more than ten years in tectonically active regions of the eastern Mediterranean coast notably in Greece, Turkey and Syria as well as in so-called stable areas of the western Mediterranean area, we have made a wide use of biological sea-level indicators (BioS.L.I.) as markers of past sea-levels. These are mainly coralline algae and invertebrates whose skeletons are well preserved as in the case of a rapid uplift of the coast, but much less so in the case of slow elevation or of submersion, whatever the velocity of the displacement. BioS.L.I. include reef-building species as well as solitary forms and boring species. Some BioS.L.I. are best adapted to the detection of slow relative movements (tectonic or eustatic) whereas others allow an accurate reconstitution of very rapid, co-seismic elevations or (more rarely) submergences. Examples put into evidence the ability of BioS.L.I. for the reconstitution of rapid and complex vertical relative movements as well as for simple monitoring of sea-level on coasts subjected to severe seismic hazard. A specific approach allows a comparative study of the possibilities offered by the principal species which may be used as BioS.L.I. in the Mediterranean area.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0040.008
Open science0.0040.005
Research integrity0.0080.004
Insufficient payload (model declined to judge)0.9910.992

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 head0.009
GPT teacher head0.160
Teacher spread0.151 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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

Citations171
Published2000
Admission routes1
Has abstractyes

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