{"id":"W4389074459","doi":"10.5194/hess-2023-143-ac1","title":"Reply on RC1","year":2023,"lang":"en","type":"peer-review","venue":"","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Hydro-Québec","keywords":"Streamflow; Calibration; Snowmelt; Environmental science; Metric (unit); Snow; Water balance; Precipitation; Watershed; Mean squared error; Hydrological modelling; Meteorology; Remote sensing; Hydrology (agriculture); Computer science; Climatology; Mathematics; Geography; Statistics; Geology; Drainage basin; Machine learning; Cartography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.002837626,0.0009609222,0.001157632,0.001125766,0.00323596,0.004609741,0.003567099,0.02876075,0.1859575],"category_scores_gemma":[0.02884956,0.0006420898,0.001595934,0.001050717,0.002164524,0.003902889,0.002888972,0.02419225,0.1451927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004133701,"about_ca_system_score_gemma":0.003786283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008404234,"about_ca_topic_score_gemma":0.009562366,"domain_scores_codex":[0.9972377,0.0004972867,0.0002800553,0.0005392218,0.0009838421,0.0004618379],"domain_scores_gemma":[0.9929408,0.002141852,0.0002726547,0.0005355014,0.003034476,0.001074797],"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":[0.000007432082,0.000002860207,0.00002522592,0.00001427348,0.000001275458,0.00004377272,0.000008446169,0.000003810836,0.00001605809,0.0003040418,0.9976504,0.00192238],"study_design_scores_gemma":[0.00000913662,0.00000629365,0.0001537937,0.00005286043,0.00000223387,0.00005294952,0.0000503487,0.0000183288,0.0000495262,0.0004265614,0.9991697,0.000008258902],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00021701,0.001706441,0.0002558861,0.7747471,0.1791803,0.0001482995,0.0007751294,0.0004632183,0.04250663],"genre_scores_gemma":[0.002016885,0.0009000936,0.0002242978,0.8092655,0.04641098,0.0002276751,0.0002688985,0.0002225908,0.1404631],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1859575,"threshold_uncertainty_score":0.6220899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07516814119647926,"score_gpt":0.2849270221377121,"score_spread":0.2097588809412329,"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."}}