{"id":"W3037823701","doi":"","title":"Geochemical heterogeneity of rivers draining the Canadian Arctic Archipelago","year":2016,"lang":"en","type":"article","venue":"AGUFM","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Archipelago; Arctic; Oceanography; The arctic; Geography; Physical geography; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002821564,0.0001631156,0.0002533399,0.003113291,0.001778102,0.001273309,0.0004593164,0.0002646196,0.0006785745],"category_scores_gemma":[0.0009142303,0.0002012976,0.0002664952,0.003061526,0.0007280622,0.0002680713,0.000566316,0.0002001552,0.00006948234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009264874,"about_ca_system_score_gemma":0.008835492,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9787301,"about_ca_topic_score_gemma":0.9903191,"domain_scores_codex":[0.9997851,0.00002059658,0.00001349242,0.00005256762,0.00005190101,0.00007636029],"domain_scores_gemma":[0.9994022,0.00008331519,0.0000729359,0.00002099997,0.0003396293,0.00008100076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001083951,0.00002174848,0.981932,0.00003471296,0.0001124458,0.0001034649,0.001020219,0.002705669,0.004415412,0.0004754155,0.0004308105,0.008639761],"study_design_scores_gemma":[0.000001782272,0.000002787284,0.9975023,0.000007054954,0.00001396183,0.00001698996,0.0006072057,0.001087667,0.00018812,0.00003150178,0.0005342977,0.000006489418],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978998,0.000140224,0.00006886081,0.00003554997,0.000001323053,0.000004286666,0.0007104066,0.000007645483,0.001131893],"genre_scores_gemma":[0.9990048,0.00009124833,0.0001215502,0.00001124205,0.000001030208,0.000003221405,0.0004370386,0.00000342375,0.0003265373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02126986,"threshold_uncertainty_score":0.06722164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01485543469251384,"score_gpt":0.2146141480050839,"score_spread":0.19975871331257,"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."}}