{"id":"W3106846998","doi":"10.5194/egusphere-egu2020-10190","title":"Democratizing ocean technology: low-cost innovations in underwater robotics","year":2020,"lang":"en","type":"article","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Arduino; Robotics; Computer science; Underwater; Computer hardware; Artificial intelligence; Embedded system; Oceanography; Robot","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":[0.001430267,0.001035896,0.0003504576,0.001079541,0.0005763914,0.002155815,0.001592056,0.001174861,0.02524582],"category_scores_gemma":[0.002259714,0.0004589877,0.00039653,0.000995404,0.001427654,0.005175231,0.00343009,0.001561684,0.01509014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006690227,"about_ca_system_score_gemma":0.0008955615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009367201,"about_ca_topic_score_gemma":0.001327562,"domain_scores_codex":[0.9983894,0.0001948107,0.00006317802,0.0001385054,0.00110296,0.0001112637],"domain_scores_gemma":[0.9987942,0.0002042204,0.0000965514,0.0002537281,0.0004992451,0.0001520776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007929456,0.0001083849,0.0007706641,0.0007864173,0.00002085362,0.0003175458,0.0003367681,0.003525423,0.09225351,0.05829717,0.04629243,0.7972116],"study_design_scores_gemma":[0.00002887836,0.0003636482,0.001169787,0.0003639783,0.00001931718,0.0005797486,0.0002713982,0.01226229,0.04182791,0.02854778,0.914492,0.00007340933],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01691854,0.007770075,0.7399848,0.008125902,0.001694183,0.0003587132,0.0003272194,0.006502966,0.2183176],"genre_scores_gemma":[0.1284672,0.01181062,0.6973511,0.002751906,0.000928643,0.0003985895,0.0008157288,0.002420003,0.1550562],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02524582,"threshold_uncertainty_score":0.08445567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02638000242040722,"score_gpt":0.2223117172831207,"score_spread":0.1959317148627134,"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."}}