{"id":"W4399352889","doi":"10.21428/d82e957c.7c728d63","title":"Associating Landmarks from SLAM’s Visual Structure","year":2024,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007658022,0.001468294,0.001479069,0.002948462,0.0005367463,0.001436309,0.001962525,0.0008399853,0.002911684],"category_scores_gemma":[0.005299529,0.0007981833,0.001265119,0.003275494,0.0006633638,0.001809941,0.003853503,0.001528768,0.003325654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005152671,"about_ca_system_score_gemma":0.0009902535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00463845,"about_ca_topic_score_gemma":0.008316113,"domain_scores_codex":[0.9988225,0.0001306942,0.00004788861,0.0003396911,0.0004878679,0.0001713378],"domain_scores_gemma":[0.9982401,0.0002418298,0.0001747767,0.0007350143,0.0005186909,0.00008947755],"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":[0.0005171941,0.0001990036,0.01426706,0.0006403046,0.0001984267,0.0004238051,0.000706627,0.1526174,0.04124261,0.005635648,0.0112283,0.7723236],"study_design_scores_gemma":[0.00004581556,0.0003895069,0.01543095,0.0001556601,0.0001056542,0.0006028148,0.0007003405,0.901827,0.03728201,0.02669194,0.01666057,0.0001077688],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07631693,0.000639194,0.9099517,0.0001894,0.0002156728,0.0001972061,0.001326906,0.007096164,0.004066934],"genre_scores_gemma":[0.6457685,0.0003133195,0.345114,0.000159413,0.00007098577,0.0001797448,0.004453382,0.001030969,0.002909711],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00463845,"threshold_uncertainty_score":0.009740591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002822249835293688,"score_gpt":0.1972892425913894,"score_spread":0.1944669927560957,"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."}}