{"id":"W2884262854","doi":"10.1016/j.jglr.2018.07.006","title":"Development and application of a real-time water environment cyberinfrastructure for kayaker safety in the Apostle Islands, Lake Superior","year":2018,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Coastal and Marine Dynamics","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Wisconsin Sea Grant Institute, University of Wisconsin","keywords":"Cyberinfrastructure; Seascape; Environmental science; Computer science; Interactive kiosk; Meteorology; Environmental resource management; Hydrology (agriculture); Geography; Geology; World Wide Web; Data science; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001181927,0.00006307576,0.0001292065,0.00009784756,0.0001149417,0.00002645868,0.0001690534,0.00003818278,0.0004832297],"category_scores_gemma":[0.00001772359,0.00003135072,0.00002730265,0.0000763916,0.0001502242,0.00007836309,0.00003223108,0.0001308551,0.00001145095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007620679,"about_ca_system_score_gemma":0.00004193273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001243969,"about_ca_topic_score_gemma":0.005758673,"domain_scores_codex":[0.999045,0.00006373067,0.0002522598,0.00009359767,0.0003433096,0.000202163],"domain_scores_gemma":[0.9996152,0.0001167606,0.00004496465,0.00009541555,0.00007784121,0.00004984902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002109362,0.0000823324,0.3706709,0.0001264624,0.00007259458,0.00002629994,0.01170538,0.0002384732,0.01082487,0.0001018347,0.0009033636,0.6031381],"study_design_scores_gemma":[0.0007545418,0.0006723495,0.747033,0.00002435281,0.00000903565,0.0001108132,0.0006183752,0.003698231,0.00116081,0.0006622997,0.2451591,0.00009706565],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963677,0.00002807158,0.0001941296,0.0003438979,0.00002196867,0.0002316285,0.0000459571,0.00000117796,0.002765489],"genre_scores_gemma":[0.9968132,0.0001218557,0.002228549,0.00001645142,0.0001142015,0.000002394387,0.00005177758,0.000002879881,0.0006487152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6030411,"threshold_uncertainty_score":0.5291027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01530976245289096,"score_gpt":0.2559006662814161,"score_spread":0.2405909038285252,"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."}}