{"id":"W4206666853","doi":"10.3389/fmars.2021.635922","title":"argoFloats: An R Package for Analyzing Argo Data","year":2021,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada; Dalhousie University","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Argo; Upload; Computer science; R package; Variety (cybernetics); Database; Data science; Data mining; World Wide Web; Artificial intelligence","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":[0.004280846,0.001908382,0.001890256,0.002493099,0.0006154024,0.002835547,0.002495882,0.0007865821,0.07982811],"category_scores_gemma":[0.02405416,0.001137736,0.002144273,0.002260831,0.0008960557,0.002118649,0.002899956,0.002675346,0.06474757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005205508,"about_ca_system_score_gemma":0.002134798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002603078,"about_ca_topic_score_gemma":0.003666885,"domain_scores_codex":[0.9979106,0.0007955023,0.0002181458,0.0004366323,0.0004640933,0.0001750749],"domain_scores_gemma":[0.9910121,0.005685448,0.0008873031,0.001256404,0.0007754259,0.0003832809],"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":[0.0005019255,0.00005469004,0.008837172,0.002413489,0.000813645,0.0004265638,0.0004288552,0.01005942,0.005426465,0.01312826,0.8707259,0.08718351],"study_design_scores_gemma":[0.0002865439,0.0001244955,0.009363577,0.0004534784,0.0002883102,0.0005978988,0.0001269139,0.02573009,0.009152983,0.0351185,0.9185119,0.0002452052],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.005534986,0.001076302,0.4473098,0.001040686,0.0007343722,0.0004430487,0.2457983,0.2854628,0.01259959],"genre_scores_gemma":[0.0390175,0.001083656,0.4513173,0.001779492,0.0003921576,0.003033522,0.210189,0.2798933,0.01329419],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.07982811,"threshold_uncertainty_score":0.2670516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02052644641762589,"score_gpt":0.248388535895807,"score_spread":0.2278620894781811,"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."}}