{"id":"W3088291244","doi":"10.1109/tro.2020.3021241","title":"SLAAM: Simultaneous Localization and Additive Manufacturing","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Odometry; Computer vision; Planar; Artificial intelligence; Scanner; Computer science; Point (geometry); Representation (politics); Object (grammar); Frame (networking); Computer graphics (images); Mathematics; Mobile robot; Geometry; Robot","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":[0.0005659898,0.0008752341,0.0007859434,0.001188491,0.0003931149,0.00128706,0.001567884,0.001180299,0.003505565],"category_scores_gemma":[0.001449877,0.0005223886,0.0008364732,0.001295413,0.0008132213,0.001509838,0.002777664,0.0009732387,0.002139072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003267484,"about_ca_system_score_gemma":0.0006183956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009722618,"about_ca_topic_score_gemma":0.001229127,"domain_scores_codex":[0.9988222,0.0001362216,0.00004062388,0.0001505849,0.0007527668,0.00009769729],"domain_scores_gemma":[0.999492,0.0001388049,0.0000595515,0.0001656226,0.0001147754,0.00002919882],"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":[0.00040956,0.0001088252,0.000850992,0.0003524047,0.00009979158,0.000443903,0.0002105074,0.08380116,0.09784875,0.02297918,0.008606647,0.7842883],"study_design_scores_gemma":[0.00008819341,0.000398387,0.0008311045,0.00006108612,0.00003843816,0.0007919654,0.00009160411,0.8612883,0.07770521,0.01667381,0.04194656,0.0000853766],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005508544,0.0003193023,0.9872497,0.0001022108,0.0001304917,0.00002467693,0.00005285338,0.0043539,0.002258416],"genre_scores_gemma":[0.2771256,0.0005427798,0.7138706,0.0001947323,0.0001578146,0.0001346697,0.0003300094,0.0004598026,0.007183985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003505565,"threshold_uncertainty_score":0.01172727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185175263421207,"score_gpt":0.1959021280471832,"score_spread":0.1840503754129711,"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."}}