{"id":"W2050913311","doi":"10.1109/ssrr.2012.6523887","title":"Dog and snake marsupial cooperation for urban search and rescue deployment","year":2012,"lang":"en","type":"article","venue":"","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Rubble; Urban search and rescue; Robot; Tree traversal; Terrain; Search and rescue; Software deployment; Rescue robot; Computer science; Flexibility (engineering); Mobile robot; Watercraft; Graph traversal; Simulation; Human–computer interaction; Artificial intelligence; Engineering; Geography; Marine engineering; Civil engineering","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":[0.0001258309,0.0000575078,0.00005676429,0.00002036808,0.00004344357,0.00003254096,0.00002209914,0.00003168937,0.00004945651],"category_scores_gemma":[0.00000586334,0.00004711143,0.000008179149,0.00002099828,0.00001245458,0.00009556252,0.00001469878,0.00003644585,0.000004921727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000105743,"about_ca_system_score_gemma":0.000002525535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003292695,"about_ca_topic_score_gemma":0.00004177983,"domain_scores_codex":[0.999649,0.000006141735,0.00007284852,0.00006939921,0.00004818163,0.0001543795],"domain_scores_gemma":[0.9998356,0.00001454676,0.000001422157,0.00006196817,0.00001596405,0.00007046815],"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":[0.0001498263,0.0002503548,0.07497651,0.001203612,0.0003227782,0.000005289896,0.01038281,0.08124853,0.1096374,0.2453397,0.03964505,0.4368381],"study_design_scores_gemma":[0.0007728265,0.0002084863,0.01578439,0.00002883676,0.00003154769,0.00002544488,0.0002027578,0.8278584,0.1125877,0.00009704709,0.04185931,0.0005432452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7637485,0.0009207065,0.2339088,0.00008978386,0.0001766574,0.0002780517,0.000004087706,0.00007593378,0.0007974402],"genre_scores_gemma":[0.9958107,0.0001300247,0.00331393,0.00003530434,0.0001277429,0.00001681943,0.000004523607,0.00001247447,0.0005484653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7466099,"threshold_uncertainty_score":0.1921148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02498078159244014,"score_gpt":0.2569064848391487,"score_spread":0.2319257032467086,"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."}}