{"id":"W2548655573","doi":"10.1109/tic-sth.2009.5444444","title":"Effects of cue saliency in an assisted target detection system for search and rescue","year":2009,"lang":"en","type":"article","venue":"","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Waterloo","funders":"Defence Research and Development Canada","keywords":"Visual search; Computer science; Task (project management); Computer vision; Brightness; Artificial intelligence; Sensory cue; Target acquisition; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003780114,0.0000727027,0.0001265345,0.0001974914,0.00006724776,0.00005026756,0.0001528213,0.0000589071,6.640978e-7],"category_scores_gemma":[0.00002509612,0.00006361752,0.00003257193,0.0003700954,0.00001322465,0.0003851683,0.00002203141,0.00005689777,0.000001400701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004127819,"about_ca_system_score_gemma":0.00001461771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008679714,"about_ca_topic_score_gemma":0.0001208177,"domain_scores_codex":[0.9991145,0.0001189568,0.000202121,0.0002589191,0.0001507435,0.00015472],"domain_scores_gemma":[0.9996493,0.00003701755,0.00002377042,0.000154675,0.00007710185,0.00005814207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007213715,0.0003327556,0.001010511,0.0004017863,0.000005733205,0.000004403042,0.0006321777,0.0002645699,0.7643387,0.01885509,0.000005877916,0.2140763],"study_design_scores_gemma":[0.0008598184,0.001461394,0.1930166,0.00005342432,0.000003493534,0.00001621718,0.0001082853,0.3254693,0.4784814,0.0003974952,0.00001142426,0.0001211568],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5371491,0.00001642151,0.4622855,0.000035561,0.0001119793,0.0002371059,2.263742e-7,0.00007535295,0.00008875872],"genre_scores_gemma":[0.9915271,0.000001804554,0.008357191,0.00003136376,0.0000168721,0.00001654239,6.879186e-7,0.000003069543,0.00004532899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4543781,"threshold_uncertainty_score":0.2594247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01643402314791299,"score_gpt":0.2926726337085467,"score_spread":0.2762386105606337,"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."}}