{"id":"W4220867366","doi":"10.1109/iccve52871.2022.9743123","title":"RainbowTag: a Fiducial Marker System with a New Color Segmentation Algorithm","year":2022,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fiducial marker; Artificial intelligence; Computer vision; Computer science; Segmentation; Robustness (evolution)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005293551,0.0008422514,0.0007092485,0.001445869,0.0003738473,0.001117676,0.002460768,0.0009323317,0.004609205],"category_scores_gemma":[0.001369454,0.0005585792,0.0006003369,0.001051671,0.0005722105,0.001934278,0.001736634,0.001081446,0.00372155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006038072,"about_ca_system_score_gemma":0.0006964055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001703402,"about_ca_topic_score_gemma":0.00167006,"domain_scores_codex":[0.9993725,0.00005973566,0.00002977598,0.0001681252,0.0003091965,0.00006068973],"domain_scores_gemma":[0.9994187,0.00006747574,0.00007036806,0.0001609787,0.0002237096,0.00005863691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004633743,0.0001032426,0.001235217,0.0001788316,0.00005551733,0.0001729535,0.0001599533,0.01378907,0.2224487,0.01138169,0.01433888,0.7356726],"study_design_scores_gemma":[0.0001010791,0.0004789118,0.001893186,0.00004627295,0.0000731336,0.001477916,0.00005258365,0.617122,0.288099,0.006102822,0.08431339,0.0002397675],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00285936,0.00009451131,0.9894421,0.00003479746,0.00006108415,0.00003044551,0.00005286876,0.006505081,0.0009198493],"genre_scores_gemma":[0.06989559,0.0001472533,0.9247307,0.0001447117,0.00005428294,0.0000648079,0.0005105477,0.0009780094,0.003474193],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004609205,"threshold_uncertainty_score":0.0154193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006065922952451964,"score_gpt":0.1809617966627208,"score_spread":0.1748958737102689,"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."}}