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Record W7014610580

Povoamento e sepulturas do Neolítico Antigo no Centro Histórico de Lisboa

2024· article· en· W7014610580 on OpenAlexaboutno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeological and Geological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHuman settlementExcavationQuarter (Canadian coin)PortugueseScope (computer science)Settlement (finance)
DOInot available

Abstract

fetched live from OpenAlex

In recent years, information regarding the human presence during the Early Neolithic period in the Historic Center of Lisbon has increased, as a result of numerous preventive archaeological excavations carried out within the scope of mitigating impacts resulting from the recovery of old buildings or the construction of new ones. Such work, carried out by several Archeology companies that have worked in areas considered to be of greatest archaeological sensitivity within the city of Lisbon, have led to results of exceptional relevance for the knowledge of the first producing societies that occupied this territory from the last quarter of the 6th millennium BC. Thus, not only large settlements were identified, such as Encosta de Sant’Ana and Bairro Alto, integrating several loci, such as Palácio Ludovice. The first structured graves known in Portuguese territory at this time were also identified, in close association with the inhabited spaces, corresponding to individual depositions in the fetal position carried out at the bottom of small graves excavated in the geological substrate. The importance of these discoveries justified the presentation of this synthesis, which summarizes all the information published to date.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.009
Science and technology studies0.0040.004
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.083
GPT teacher head0.362
Teacher spread0.280 · 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 designObservational
Domainnot available
GenreEmpirical

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 routes1
Has abstractyes

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