MétaCan
Menu
Back to cohort
Record W2997288674

Ámbar: una gema de interés comercial, histórico y químico

2019· article· es· W2997288674 on OpenAlexaboutno aff
José Eduardo Báez García, Vanessa Vargas-Alfaro, J. Óscar C. Jiménez‐Halla

Bibliographic record

VenueNaturaleza y Tecnología · 2019
Typearticle
Languagees
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhysicsArt
DOInot available

Abstract

fetched live from OpenAlex

El ambar es un material antiguo que ha sido utilizado en joyeria desde civilizaciones antiguas. Ademas, el ambar ha demostrado ser un medio de preservacion de especies extintas que vivieron hace millones de anos como insectos, aracnidos y reptiles. El ambar es una resina fosilizada que esta formada de una mezcla compleja de compuestos organicos llamados terpenos y que originalmente eran parte de una resina exudada por arboles hace millones de anos. El ambar procedente de arboles de la familia de la conifera presenta como caracteristica un contenido apreciable de acido succinico como el caso del ambar de Rusia (ambar baltico), Alemania y Canada. Sin embargo, el ambar procedente de la familia de las leguminosas como por ejemplo el ambar de Mexico y Republica dominicana no contienen acido succinico. Actualmente muchos de los terpenos encontrados en el ambar se pueden encontrar como productos naturales de la familia de las coniferas y algunos de estos compuestos han sido utilizados en la sintesis de monomeros y polimeros.

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)0.001
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 score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.006

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 head0.010
GPT teacher head0.292
Teacher spread0.282 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueNaturaleza y TecnologíaSame topicHistorical and Literary StudiesFrench-language works237,207