{"id":"W4298112138","doi":"10.1109/ro-man53752.2022.9900567","title":"Bots of a Feather: Exploring User Perceptions of Group Cohesiveness for Application in Robotic Swarms","year":2022,"lang":"en","type":"article","venue":"2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","topic":"Insect and Arachnid Ecology and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Group cohesiveness; Swarm behaviour; Computer science; Human–computer interaction; Perception; Context (archaeology); Animation; Group (periodic table); Robot; Swarm robotics; Artificial intelligence; Psychology; Social psychology","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":[0.0002146939,0.0001221588,0.0001801414,0.0001581642,0.0001990154,0.00001487351,0.0004215754,0.00005564175,0.0001986907],"category_scores_gemma":[0.00001878307,0.0001357178,0.00008409586,0.0000592517,0.000116158,0.00002816081,0.0001865844,0.0002099138,0.000001322801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005833948,"about_ca_system_score_gemma":0.00002994728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001220757,"about_ca_topic_score_gemma":0.0004813746,"domain_scores_codex":[0.9990813,0.0001338509,0.0003164285,0.0002402811,0.0001197657,0.0001083626],"domain_scores_gemma":[0.9991586,0.00006400675,0.0002592682,0.000295658,0.0001985726,0.00002388342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005945188,0.001056533,0.03061134,0.00002912915,0.0001040779,7.336839e-7,0.001327919,0.001982125,0.9306936,0.03168601,0.0002026677,0.001711406],"study_design_scores_gemma":[0.01266451,0.008811946,0.4684647,0.0008224447,0.0004105054,0.0000858543,0.03615478,0.01894076,0.4267204,0.0131827,0.01108762,0.002653793],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959404,0.00004307089,0.002650022,0.0002725546,0.0001730629,0.0003899122,0.00005457325,0.000009260613,0.0004671133],"genre_scores_gemma":[0.9975076,0.0001488459,0.0002311293,0.00009259136,0.00003445208,0.001018581,0.0005665241,0.00001704825,0.0003832292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5039731,"threshold_uncertainty_score":0.5534409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06934420514750014,"score_gpt":0.3432867875391541,"score_spread":0.273942582391654,"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."}}