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Record W7067885014

Nuove ecologie / Nuovi significati

2024· article· it· W7067885014 on OpenAlexaboutno aff

Bibliographic record

VenueIRIS Research product catalog (Sapienza University of Rome) · 2024
Typearticle
Languageit
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodTSG101LiquationFusible alloyArticular cartilage damage
DOInot available

Abstract

fetched live from OpenAlex

Nel dicembre 2022 la COP15 per la Biodiversità ha approvato il Kunming-Montreal Global Biodiversity Fra-mework, un protocollo per la protezione degli ecosistemi planetari che si affianca al Paris Agreement on Climate Change con l’obiettivo di scongiurare il col-lasso della biosfera. Una rete globale di aree a diversi gradi di naturalità e antropizzazione, capace di arrestare la perdita di biodiversità e abbattere la concentrazione di anidride carbonica in atmosfera, dovrà estendersi sul 30% della Terra entro il 2030 e consoli-darsi ulteriormente al 2050. L’accordo solleva una molteplicità di tematiche che il progetto del paesaggio ingaggia: la conservazione delle specie e degli ecosistemi della biosfera; la riqualificazione ambientale di aree terrestri e mari-ne degradate; la gestione equa delle terre ancestrali e i diritti delle popolazioni indigene; la tutela dei paesaggi culturali e il sostegno alle comunità locali; l’abbandono tanto dello sfruttamento insostenibile dei territori, quanto di musealizzazioni e vernacolarizzazioni al servizio del turismo globale; il potenziamento dei contributi ecologici di aree degradate, sfruttate o sottoutilizzate, ai margini abitati o negli hinterland operativi dell’urbanizzazione planetaria; l’accompagnamento dei sistemi antro-ecologici della contemporaneità verso nuove forme di equilibrio, convenzionalmente definite dai termini di sosteniibilità e resilienza.

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)0.004
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.057
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0080.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0570.008

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 head0.056
GPT teacher head0.328
Teacher spread0.272 · 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
Published2024
Admission routes1
Has abstractyes

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