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The Effects and Mechanism of Yinqiao Powder on Upper Respiratory Tract Infection

2015· article· en· W1576031517 on OpenAlexvenueno aff
Xiao-Hua Duan, Li-Song Liu, Na Lei, Qing Lin, Wei-Li Wang, Han-Wen Yan

Bibliographic record

VenueInternational Journal of Biotechnology for Wellness Industries · 2015
Typearticle
Languageen
FieldHealth Professions
TopicPediatric health and respiratory diseases
Canadian institutionsnot available
FundersChengdu UniversityChengdu University of Traditional Chinese MedicineYunnan University
KeywordsMechanism (biology)Respiratory tractMedicineUpper respiratory tract infectionRespiratory systemImmunologyInternal medicinePhilosophy

Abstract

fetched live from OpenAlex

Kemampuan spasial visual bagi anak jalanan diyakini akan dapat membantu mereka mengembangkan potensi diri dan berkontribusi lebih bagi masyarakat. Penelitian ini bertujuan untuk mendeskripsikan bagaimana kondisi kecerdasan spasial visual anak jalanan yang berada pada naungan Yayasan Bali Street Mums and Kids Denpasar. Metode penelitian menggunakan pendekatan kualitatif yang disajikan secara deskriptif. Metode menggambar dengan dan tanpa instruksi digunakan untuk menganalisis bagaimana deskripsi kecerdasan spasial pada objek kasus. Variabel penilaian berupa tingkat kesesuaian dengan komposisi, proporsi dan teknik perspektif objek. Melalui hasil penelitian ditemukan bahwa anak jalanan pada rentang usia 0-7 tahun cenderung lebih banyak menggunakan imajinasinya dalam memvisualkan objek, sehingga lemah dalam proporsi dan detail, serta belum mengetahui tentang kedalaman objek. Rentang usia 8-12 tahun lebih mendetail dalam menggambar dengan instruksi, sudah lebih proporsional dan mengenal kedalaman objek, namun kurang dalam memvisualkan imajinasinya. Rentang usia 13-16 tahun menunjukkan variasi yang lebih tinggi antara yang sudah mampu dan yang belum mampu memvisualkan dengan baik sehingga faktor keterampilan menggambar menjadi faktor yang berpengaruh. Penguatan kecerdasan spasial visual agar difokuskan pada rentang usia 8-12 tahun.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.391
Teacher spread0.339 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations25
Published2015
Admission routes1
Has abstractyes

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