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Record W2073988609 · doi:10.1177/105971230601400101

Collective Robotic Site Preparation

2006· article· en· W2073988609 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

VenueAdaptive Behavior · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRobotComputer scienceConstruct (python library)Task (project management)Artificial intelligenceMars Exploration ProgramNest (protein structural motif)Ant colonyHuman–computer interactionAnt colony optimization algorithmsEngineeringSystems engineeringBiology

Abstract

fetched live from OpenAlex

Robotic site preparation has been identified as an integral precursor to human landings on Mars. Many species of social insect carry out the site preparation task when they construct their nests. A site preparation algorithm was developed based on the nest construction behavior of a particular spe cies of ant, Leptothorax albipennis. In this paper, we present a new approach to modeling the tempo ral behavior of a multiple-robot system and apply it to our construction algorithm. In order to validate our model, experiments with multiple physical robots were conducted. Not only did the results of our experiments closely follow the predictions of our model, but the sites prepared by our robots appeared very similar to the nests built by the ants that were our inspiration.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.539

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 studies0.0000.000
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 head0.013
GPT teacher head0.258
Teacher spread0.246 · 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