{"id":"W2995303021","doi":"","title":"Variability and trends in streamflow input to Hudson Bay, Canada","year":2010,"lang":"en","type":"article","venue":"EGUGA","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Bay; Streamflow; Geography; Environmental science; Climatology; Oceanography; Geology; Cartography; Drainage basin","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":[0.0003997226,0.0002154312,0.000263285,0.001375827,0.001073703,0.001433904,0.000683251,0.0002989079,0.001913373],"category_scores_gemma":[0.00184634,0.0002432335,0.0002726967,0.002428221,0.0005439169,0.0003358241,0.0005912492,0.0004241222,0.0002595544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01579633,"about_ca_system_score_gemma":0.01390005,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9905699,"about_ca_topic_score_gemma":0.9951643,"domain_scores_codex":[0.999625,0.00002627823,0.00002847195,0.00007838247,0.0001259202,0.0001159069],"domain_scores_gemma":[0.9981316,0.0001789186,0.0001670472,0.00005197939,0.001135166,0.0003353468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001161911,0.00003181111,0.9902281,0.00001783438,0.00008204996,0.00009360672,0.0006268121,0.0007300351,0.0007030884,0.0001536011,0.001971712,0.005245216],"study_design_scores_gemma":[0.000003878877,0.000004067867,0.9983401,0.000006534993,0.000008566909,0.00001268546,0.0004055756,0.0004608689,0.00007211554,0.00001088587,0.0006705837,0.000003986092],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951324,0.0002059266,0.00005199245,0.0001934322,0.00001803095,0.000006972679,0.002687285,0.00001801555,0.001685942],"genre_scores_gemma":[0.9961577,0.0002048641,0.00008303482,0.00004779,0.000006543932,0.000004212897,0.001377168,0.000007454513,0.002111309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01579633,"threshold_uncertainty_score":0.114611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004364285013999866,"score_gpt":0.1895567528244571,"score_spread":0.1851924678104572,"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."}}