{"id":"W2960081125","doi":"10.1145/3306346.3322942","title":"Multi-robot collaborative dense scene reconstruction","year":2019,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"Google (Canada); University of Waterloo","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Robot; Computer science; Benchmark (surveying); Task (project management); Artificial intelligence; Computer vision; Set (abstract data type); Engineering","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":[0.00006682755,0.0001617576,0.0001495033,0.0002463579,0.0001150213,0.00003758952,0.0001101577,0.000149765,0.0001228288],"category_scores_gemma":[0.00001191806,0.0001734303,0.00007586412,0.000707538,0.00004271888,0.0001427707,0.000001199754,0.0002449643,0.000159381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005296271,"about_ca_system_score_gemma":0.00002309623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009756652,"about_ca_topic_score_gemma":0.00008271076,"domain_scores_codex":[0.9992482,0.00003275329,0.0002030663,0.0001902778,0.00014427,0.0001814479],"domain_scores_gemma":[0.9993105,0.00007151929,0.00002778999,0.000393648,0.0001259314,0.00007060847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002354642,0.00007218695,0.0004934507,0.00004068344,0.00008803006,0.000002258301,0.0002153641,0.973213,0.008747081,0.0002526632,0.00007292297,0.01677888],"study_design_scores_gemma":[0.001920448,0.0001809279,0.003073507,0.0001258253,0.000102158,0.00003020355,0.0003567407,0.9558313,0.03472896,0.000999416,0.001942367,0.0007081165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1299641,0.0001056327,0.8674823,0.0001636285,0.001322108,0.0003230379,0.00003636291,0.0003499945,0.0002528074],"genre_scores_gemma":[0.9772373,0.0005032014,0.0219429,0.000102411,0.00002267947,0.0000150181,0.00001563978,0.00004251713,0.000118332],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8472732,"threshold_uncertainty_score":0.7072282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01372179176761954,"score_gpt":0.2212299298303649,"score_spread":0.2075081380627453,"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."}}