{"id":"W4283784538","doi":"10.5194/gmd-2022-135-rc2","title":"Comment on gmd-2022-135","year":2022,"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":"University of Saskatchewan","funders":"Global Water Futures; Australian Research Council; Melbourne Water; Department of Environment, Land, Water and Planning, State Government of Victoria","keywords":"Toolbox; Computer science; Troubleshooting; Debugging; Process (computing); Modular design; Class (philosophy); Workflow; Data mining; Readability; Software engineering; Programming language; Database; Artificial intelligence; Operating system","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":[0.001841982,0.000836486,0.0007722846,0.001215919,0.001756053,0.003763661,0.001947806,0.01200607,0.2086126],"category_scores_gemma":[0.01431473,0.0004075014,0.001263326,0.00133083,0.001311164,0.002417605,0.001757844,0.008025565,0.1438124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003443263,"about_ca_system_score_gemma":0.002937518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02980887,"about_ca_topic_score_gemma":0.02479107,"domain_scores_codex":[0.9983801,0.0001414887,0.0001075022,0.0001955876,0.0009607101,0.0002147272],"domain_scores_gemma":[0.9962254,0.0009367969,0.0001798458,0.0003966833,0.001962632,0.0002987349],"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":[0.00002528678,0.000006675875,0.00004971402,0.00003948054,0.000001531901,0.00004794608,0.00001349686,0.00002671086,0.0000813333,0.001233276,0.9955516,0.002922825],"study_design_scores_gemma":[0.00001090434,0.000005485386,0.0002556282,0.00004413703,0.000001625944,0.00001632539,0.00001727849,0.00003763045,0.0001101007,0.0006150208,0.9988784,0.000007381055],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.001118206,0.001659294,0.002550697,0.3210091,0.2627272,0.000530939,0.02219773,0.008287208,0.3799196],"genre_scores_gemma":[0.006741927,0.00101633,0.002029063,0.3676806,0.02795881,0.0003763768,0.006617204,0.002853404,0.5847264],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.2086126,"threshold_uncertainty_score":0.6978788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02375079128480102,"score_gpt":0.2684896643293366,"score_spread":0.2447388730445356,"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."}}