{"id":"W2073818951","doi":"10.5555/2157848.2157850","title":"AntReckoning: dead reckoning using interest modeling by pheromones","year":2011,"lang":"en","type":"article","venue":"","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Dead reckoning; Computer science; Motion (physics); Inertia; Key (lock); Quake (natural phenomenon); Artificial intelligence; Simulation; Computer security; Telecommunications; Global Positioning System","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002771659,0.0002256891,0.0002218335,0.0001824056,0.0001619435,0.0001736214,0.001759932,0.0001222643,0.00002447194],"category_scores_gemma":[0.00008027549,0.0002082591,0.00005549542,0.0006264407,0.00004177971,0.0006736206,0.001074305,0.0002168082,0.00007213812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007119295,"about_ca_system_score_gemma":0.00003274007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004035866,"about_ca_topic_score_gemma":0.00007040789,"domain_scores_codex":[0.9983155,0.00003559756,0.0003051861,0.0005848815,0.0001913037,0.0005676004],"domain_scores_gemma":[0.99889,0.00003846241,0.00007304666,0.0007905852,0.00008763607,0.000120298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009025427,0.0005529119,0.009048515,0.0000517738,0.0002662276,0.0002737426,0.01259931,0.01478756,0.08789112,0.1538955,0.01994688,0.7005962],"study_design_scores_gemma":[0.0001198543,0.00007512952,0.0000253847,0.00007839718,0.000005940761,0.00003181691,0.0002075135,0.9622648,0.03177301,0.004626221,0.0004227189,0.0003691702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2593713,0.0002436771,0.7348952,0.0002516377,0.0002580697,0.00008632238,5.85173e-7,0.00118861,0.003704699],"genre_scores_gemma":[0.5822878,0.000005722139,0.4173512,0.0001593912,0.00002064489,0.00000490117,4.982696e-7,0.00001316584,0.0001566405],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9474773,"threshold_uncertainty_score":0.8492561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1727910987967993,"score_gpt":0.2780754227255378,"score_spread":0.1052843239287384,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}