{"id":"W4385481416","doi":"10.5194/egusphere-2023-1521-ac1","title":"Reply on RC1","year":2023,"lang":"en","type":"peer-review","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Ministère des Forêts, de la Faune et des Parcs","keywords":"STREAMS; Hydrology (agriculture); Surface runoff; Watershed; Bottleneck; Hydrography; Channel (broadcasting); Infiltration (HVAC); Scale (ratio); Environmental science; Computer science; Algorithm; Geology; Geography; Ecology; Machine learning; Meteorology; Cartography; Geotechnical engineering","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":[0.003414352,0.0008347228,0.001100966,0.001419191,0.002932862,0.003818578,0.003189869,0.02794363,0.0926158],"category_scores_gemma":[0.04499102,0.0005631877,0.001166616,0.001069718,0.00209648,0.003931139,0.002438296,0.02083561,0.07390004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004381996,"about_ca_system_score_gemma":0.003994034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01025111,"about_ca_topic_score_gemma":0.01175455,"domain_scores_codex":[0.9969509,0.0005574934,0.0003979221,0.0005073088,0.001167511,0.0004189209],"domain_scores_gemma":[0.9862098,0.004559702,0.0005327691,0.0007033629,0.006341907,0.001652374],"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":[0.000009448564,0.000003021968,0.00004818233,0.00001755586,0.000001632102,0.00007604131,0.00001333463,0.000004103129,0.00002045524,0.0002478474,0.9976512,0.001907314],"study_design_scores_gemma":[0.00001128036,0.000008081723,0.0002663585,0.00006740117,0.000003693137,0.0001348614,0.0000792947,0.00002827712,0.0000758286,0.0004784546,0.9988323,0.00001410782],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0001896281,0.001161563,0.0001709302,0.8697387,0.1162929,0.00007828054,0.0003819117,0.0002418702,0.01174418],"genre_scores_gemma":[0.002459547,0.001017933,0.000215771,0.8793638,0.05329664,0.0001537147,0.0001855746,0.0001636516,0.0631433],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0926158,"threshold_uncertainty_score":0.3098307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03241635041228617,"score_gpt":0.2825835911227242,"score_spread":0.2501672407104381,"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."}}