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Record W17150915 · doi:10.1093/nass/nrl128

HP GRANTS FOR TABLET TECHNOLOGIES IN SCIENCE TEACHING: FROM DREAM TO INNOVATION

2010· article· en· W17150915 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsToronto Metropolitan UniversityUniversity of British Columbia
Fundersnot available
KeywordsDreamClass (philosophy)Mathematics educationMobile deviceComputer sciencePsychologyWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

The peroxisome proliferator-activated receptors (PPARs) are ligand-activated transcription factors that belong to the nuclear hormone receptor superfamily. PPARalpha is mainly expressed in the liver, kidney, heart and muscle. PPARalpha activates fatty acid catabolism, stimulates gluconeogenesis and ketone body synthesis and is involved in the control of lipoprotein assembly. Although PPARalpha is well characterized in the liver, its physiological function is unknown in the kidney. To investigate the intimate function of PPARalpha in the kidney, we analyzed the target gene expression in human metastatic renal cell carcinoma cell line, Caki-1, using small interfering RNA (siRNA) against PPARalpha and real-time RT-PCR methods. We found that some selected genes (long-chain fatty-acid-CoA ligase (FACL1), carnitine palmitoyltransferase 1A (CPT1A), adipose differentiation-related protein (ADRP) and aquaporin 3 (AQP3)) were down-regulated by PPARalpha siRNA. These results suggest that PPARalpha regulates fatty acid metabolism and body water homeostasis in this cell line.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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

Quick stats

Citations3
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicExperimental Learning in EngineeringFrench-language works237,207