{"id":"W4238458588","doi":"10.1109/crv18844.2011","title":"2011 Canadian Conference on Computer and Robot Vision","year":2011,"lang":"en","type":"paratext","venue":"","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Robot; Artificial intelligence; Computer vision; Robot vision; Computer graphics (images); Human–computer interaction; Mobile robot","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001669105,0.001697773,0.001899577,0.002299499,0.001930595,0.006467337,0.00256027,0.002538889,0.2880231],"category_scores_gemma":[0.00389505,0.0007571356,0.0007195854,0.003250068,0.001806783,0.003698882,0.002253022,0.002536362,0.1651805],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00356078,"about_ca_system_score_gemma":0.01169453,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1471903,"about_ca_topic_score_gemma":0.2354682,"domain_scores_codex":[0.9987596,0.0001340137,0.00005320431,0.0001683151,0.0007236259,0.0001611642],"domain_scores_gemma":[0.996825,0.0003895368,0.00004969996,0.0005244571,0.001856265,0.0003550653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007793069,0.00004846165,0.0001430527,0.00018701,0.00001403506,0.00004758345,0.00003576689,0.001578567,0.0007215093,0.01020851,0.766205,0.2207326],"study_design_scores_gemma":[0.00001497608,0.00002287642,0.0006877597,0.0001125961,0.00002115715,0.00009129589,0.0001033327,0.01430422,0.001276186,0.01052743,0.9728098,0.00002834587],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.005142951,0.01888529,0.2878916,0.01572566,0.01981364,0.0003881027,0.01030545,0.02235639,0.619491],"genre_scores_gemma":[0.0127509,0.01017983,0.02834396,0.000451726,0.0005704326,0.0001157041,0.006478638,0.001261396,0.9398475],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9964392,"threshold_uncertainty_score":0.9635334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02235067433213652,"score_gpt":0.2156395791474799,"score_spread":0.1932889048153433,"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."}}