{"id":"W2311636373","doi":"10.1515/9780889774322-007","title":"Arctic Data Streams: Graphing Land and Love","year":2016,"lang":"en","type":"article","venue":"University of Regina Press eBooks","topic":"Health and Medical Research Impacts","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Association of Emergency Physicians","funders":"","keywords":"STREAMS; Arctic; The arctic; Hydrology (agriculture); Geography; Oceanography; Geology; Computer science; Geotechnical 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":[0.0002874027,0.00005571579,0.0001455742,0.0000676871,0.00003296989,0.000003206475,0.0001492182,0.00005279547,0.00001890209],"category_scores_gemma":[0.001424266,0.00003949532,0.00001759289,0.00001324672,0.0003041444,0.00007860854,0.0001756964,0.0001002996,0.000004363439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003008662,"about_ca_system_score_gemma":0.0003842187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009444823,"about_ca_topic_score_gemma":0.00005599886,"domain_scores_codex":[0.9992357,0.00003561546,0.00003842545,0.0001715763,0.0002347646,0.0002839473],"domain_scores_gemma":[0.9981552,0.000172094,0.00003766687,0.0003881507,0.00006173817,0.001185168],"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":[0.002185826,0.0001425469,0.0713729,0.002470339,0.0002491731,0.0009785382,0.001793394,6.632189e-8,0.002926909,0.002240151,0.1138146,0.8018256],"study_design_scores_gemma":[0.003947669,0.0003507397,0.005766989,0.001032035,0.00007716729,0.00004142298,0.000205368,0.0000680442,0.000428087,0.000092177,0.9879063,0.00008402336],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8478373,0.0008873706,0.002535698,0.06989153,0.00008644135,0.000852149,0.0001657021,0.00007417627,0.07766959],"genre_scores_gemma":[0.9676833,0.001333137,0.0005737843,0.0002771566,0.00004943168,5.052919e-8,0.000008492736,0.000007812389,0.0300669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8740917,"threshold_uncertainty_score":0.1705082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1445788432456271,"score_gpt":0.3332533086227062,"score_spread":0.1886744653770792,"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."}}