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Record W26302103 · doi:10.1037/pas0000140

Coordination and adaptation in impromptu teams

2005· article· en· W26302103 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

VenueNational Conference on Artificial Intelligence · 2005
Typearticle
Languageen
FieldComputer Science
TopicMulti-Agent Systems and Negotiation
Canadian institutionsUniversity of Alberta
FundersFundación Florencio Fiorini
KeywordsImpromptuComputer scienceTeamworkJoinsAdaptation (eye)RobotAdversarial systemKey (lock)Multi-agent systemHuman–computer interactionDomain (mathematical analysis)Knowledge managementArtificial intelligenceComputer security

Abstract

fetched live from OpenAlex

The present work was aimed at analyzing the psychometric properties of a Spanish version of the 48-item Young Adult Alcohol Consequences Questionnaire (YAACQ) by applying the item response theory. Participants were 247 college students (75.7% female) who reported drinking alcohol within the last 3 months. The 48-item YAACQ was translated into Spanish and back to English. The psychometric properties of the Spanish YAACQ (S-YAACQ) were analyzed applying the Rasch model, as well as group difference and correlational analyses. Factor structure of the S-YAACQ was analyzed using confirmatory factor analysis. The verification of the global fit of the data showed adequate indexes for persons and items. The reliability estimates for the items and the persons were both high. Scores on the S-YAACQ were strongly correlated with scores on the Spanish versions of the AUDIT and the RAPI and with frequency of binge drinking. Five of 48 items showed different item functioning (DIF) as a function of gender. These biases were in opposite directions, resulting in DIF cancellation. The item severity continuum was largely similar to that found with the Spanish brief YAACQ and to that found in U.S. and Dutch samples. Overall, results from the present study suggest that this translated full version is better suited than the brief YAACQ for the identification of youth who are experiencing problems with alcohol. Findings suggest that the Spanish version of the full YAACQ may be used to identify a broad diversity of alcohol-related problems in Spanish-speaking college students. (PsycINFO Database Record

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.124
GPT teacher head0.334
Teacher spread0.209 · 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