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A HISTOLOGIA COMO UMA FERRAMENTA NO ESTUDO DOS FÓSSEIS: CONSIDERAÇÕES SOBRE A PALEOHISTOLOGIA EM MAMÍFEROS COM CARAPAÇA ÓSSEA

2019· article· pt· W3010137488 on OpenAlexaff
Yumi Sakura, Édison Vicente Oliveira

Bibliographic record

VenueEstudos Geológicos · 2019
Typearticle
Languagept
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsFuture Earth
Fundersnot available
KeywordsHumanitiesBiologyPhilosophy

Abstract

fetched live from OpenAlex

Mesmo após milhões de anos de soterramento, muitos vertebrados ainda apresentam a estrutura histológica do tecido ósseo preservada. Aspectos ontogenéticos, reconheci-mento de feições fossildiagenéticas, aprimoramento de estudos sistemáticos e anatômi-cos são os principais pontos abordados pelos estudos paleohistológicos. Dentre os ver-tebrados, os grupos mais estudados por esta ótica foram os dinossauros, pterossauros, ictiossauros, crocodilomorfos, testudines, cinodontes e peixes, sendo ainda discretos os estudos realizados com mamíferos, especialmente os mamíferos com carapaça óssea. Este trabalho pretende reunir o conhecimento disponível acerca da histologia de osteo-dermos de mamíferos cingulados, de forma a apresentar um panorama dos trabalhos atuais e um ponto de partida para futuros trabalhos.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0200.063

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 head0.015
GPT teacher head0.239
Teacher spread0.225 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2019
Admission routes1
Has abstractyes

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