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Record W2360865002

Strongly Projecting Nasal Bones and Climatic Adaptation of Nanjing Homo erectus

2009· article· en· W2360865002 on OpenAlexaboutno aff
Wu Liu

Bibliographic record

VenueActa Anthropologica Sinica · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsHomo erectusAdaptation (eye)AnatomyGeologyBiologyAeolian processesCavePaleontologyEcologyPleistoceneNeuroscience
DOInot available

Abstract

fetched live from OpenAlex

In order to argue that Nanjing Homo erectus is a cold-adapted species,the measurements of three kinds are examined. Results show that the rhinal and simotic indices are valuable but that the dacryon index is unsuitable for measuring the projection of nasal bones. The rhinal and simotic indices and climatic data in the paper by Carey and Steegmann's paper suggest that …the human nose projects more in drier areas than in humid ones,and more in cold climates than in warm ones. [10] staterment is also supported by nasal anatomy and respiratory physiology. In the Inuit people,there is a possibility of a highly efficient air-conditioning system,even though their nasal bones are not strongly projected. This system would be characterized by restricted aperture width,but an appreciably expanded internal nasal chamber,with enlarged conchae,meatuses,etc. [13] The nasal morphology of the Inuit represents another type of nasal climatic adaptation,and cannot be used as proof to contradict the relationship between strongly projecting nasal bones and climatic adaptation. Moreover,pollen,spores and phytoliths from cave deposits indicate a cold glacial environment,which is comparable to that of a major ice age. To summarize,it is the most reasonable explanation so far that the strongly projecting nasal bones of Nanjing Homo erectus are the product of climatic adaptation rather than of gene flow.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.296
Teacher spread0.259 · 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 teacher head, not a consensus.

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

Citations1
Published2009
Admission routes1
Has abstractyes

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