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Risk Factors for Adolescent Academic Achievement (pdf)

2003· article· en· W8206130 on OpenAlexaboutno aff
Lynn Magdol

Bibliographic record

VenueEuropean Journal of Pharmacology · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Substance Use and School Attendance
Canadian institutionsnot available
Fundersnot available
KeywordsUnderemploymentQuarter (Canadian coin)UnemploymentAcademic achievementPopulationAt-risk studentsAdolescent developmentPsychologyYouth unemploymentEconomic growthDemographyDevelopmental psychologyEconomicsMathematics educationSociologyGeography

Abstract

fetched live from OpenAlex

The inhibitory effect of forskolin-stimulated 3',5'-cyclic monophosphate (c-AMP) synthesis in isolated rat adipocytes has been measured for eight typical adenosine receptor agonists. The percent inhibition was evaluated using concentrations of each compound corresponding to 100 times their Ki, inhibitory binding constants, determined in parallel by [3H]N6-cyclohexyladenosine binding to adenosine A1 receptors on adipocyte rat membranes which guaranteed full receptor occupancy. Some drugs were able to inhibit the forskolin-induced c-AMP accumulation by 100% (full agonists, intrinsic activity = 1) but others only to a lesser extent, ranging from 80% to 50% (partial agonists, intrinsic activities in the 0.8-0.5 interval). These efficacy data were correlated with the thermodynamic binding parameters (free energy, enthalpy and entropy) obtained in rat brain membranes by equilibrium constant measurements and van 't Hoff plots in the 0 degrees-30 degrees C range. The positive correlation between intrinsic activity and entropy changes (r = 0.88, n = 8, P < 0.01) points to the possibility of obtaining information about the full spectrum of activities of adenosine analogues from in vitro binding assays and suggests some considerations on the possible drug-receptor interaction mechanism.

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)0.003
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.001
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 head0.049
GPT teacher head0.348
Teacher spread0.300 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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