{"id":"W4247705277","doi":"10.5194/hess-2021-233-rc1","title":"Comment on hess-2021-233","year":2021,"lang":"en","type":"peer-review","venue":"","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Jet Propulsion Laboratory; Ministry of Science and ICT, South Korea; Korea Meteorological Administration; California Institute of Technology; U.S. Department of Agriculture; National Aeronautics and Space Administration","keywords":"Soil water; Water content; Span (engineering); Gravimetric analysis; Soil science; Mean squared error; Environmental science; Mathematics; Statistics; Geotechnical engineering; Chemistry; Geology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008644188,0.0007516361,0.0007782847,0.001084106,0.001164088,0.00435269,0.001550318,0.006962433,0.2879373],"category_scores_gemma":[0.006930737,0.0004004818,0.001011609,0.001726194,0.0007518503,0.002477927,0.00154976,0.004759998,0.1663346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002160904,"about_ca_system_score_gemma":0.002491681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02541609,"about_ca_topic_score_gemma":0.02302424,"domain_scores_codex":[0.999101,0.0000832569,0.0000595925,0.0001049273,0.0004973879,0.000153908],"domain_scores_gemma":[0.9978828,0.0003591749,0.0000882016,0.0002960824,0.001217966,0.0001558332],"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":[0.00002756409,0.000003865019,0.00004887662,0.00005284686,0.000002422293,0.00003166933,0.000005544733,0.00004345585,0.00007874512,0.0006617482,0.99607,0.002973127],"study_design_scores_gemma":[0.00001598165,0.000005234614,0.0005964445,0.00005659501,0.000002666758,0.00001146134,0.00003047917,0.00008570411,0.0002240569,0.0007244296,0.9982363,0.00001065464],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.001376616,0.001912283,0.001756639,0.1882183,0.2538286,0.0005684134,0.07269574,0.006295953,0.4733474],"genre_scores_gemma":[0.01991397,0.002125842,0.001903028,0.1281272,0.03711914,0.0005407229,0.02751791,0.003405347,0.7793468],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.2879373,"threshold_uncertainty_score":0.963246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02368457738525487,"score_gpt":0.2775114548768531,"score_spread":0.2538268774915982,"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."}}