{"id":"W2736621623","doi":"10.1109/icra.2017.7989238","title":"Visual triage: A bag-of-words experience selector for long-term visual route following","year":2017,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Vocabulary; Triage; Artificial intelligence; Term (time); Computer vision; Visualization; Limiting; Human–computer interaction; Engineering; 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":[0.0001075778,0.0001527331,0.0002336127,0.00006011102,0.0001802066,0.000129298,0.0001946338,0.00008838546,0.00004066414],"category_scores_gemma":[0.0001216703,0.0001457049,0.0001383483,0.00006311093,0.00002692136,0.0002333958,0.00002639595,0.00005848603,0.000005234788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004204436,"about_ca_system_score_gemma":0.00002388044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000225216,"about_ca_topic_score_gemma":0.00003288091,"domain_scores_codex":[0.9991209,0.00001016516,0.0002655276,0.0001809343,0.0001590709,0.0002634271],"domain_scores_gemma":[0.999502,0.00005954638,0.00005977992,0.0002528708,0.00004843212,0.00007736776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004552108,0.0006173134,0.3843217,0.001154427,0.000811249,0.00009811392,0.005261236,0.2343255,0.2905035,0.004967801,0.001120516,0.07636351],"study_design_scores_gemma":[0.001598193,0.0001855491,0.02835939,0.0000700087,0.00004568876,0.000001775627,0.00006431073,0.8591068,0.1100326,0.00002163431,0.0001530782,0.0003610516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6345657,0.00003008497,0.364256,0.00001161186,0.0004863843,0.0002000791,0.000002201345,0.00009298354,0.0003549526],"genre_scores_gemma":[0.9968453,0.000009627163,0.002523365,0.00001772255,0.0001498836,0.00003126306,0.00001915293,0.00004034353,0.0003633129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6247813,"threshold_uncertainty_score":0.5941674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02117794466823345,"score_gpt":0.3212287967160142,"score_spread":0.3000508520477808,"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."}}