{"id":"W4294741338","doi":"10.5194/gmd-2022-174-rc2","title":"Comment on gmd-2022-174","year":2022,"lang":"en","type":"peer-review","venue":"","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Uppsala Universitet; Vetenskapsrådet; Svenska Forskningsrådet Formas; Norges Forskningsråd; European Commission; Joint Programming Initiative Water challenges for a changing world","keywords":"Algal bloom; Chlorophyll a; Computer science; Fish <Actinopterygii>; Bathythermograph; Nutrient; Bloom; Workflow; Machine learning; Environmental science; Oceanography; Statistics; Phytoplankton; Ecology; Fishery; Mathematics; Chemistry; Biology; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008549443,0.0003638053,0.0004998483,0.00004078022,0.0003246452,0.00003356445,0.0008157009,0.0001605003,0.5046571],"category_scores_gemma":[0.0002088317,0.0002791155,0.0002088282,0.0004022709,0.0001417374,0.00002680769,0.001324601,0.0009673571,0.00666701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007165145,"about_ca_system_score_gemma":0.00001407264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008412168,"about_ca_topic_score_gemma":0.00005650003,"domain_scores_codex":[0.9970294,0.0002187092,0.0003699712,0.0007476168,0.001177108,0.0004572193],"domain_scores_gemma":[0.9987639,0.0001647614,0.0001735297,0.0007354202,0.000004833413,0.0001576088],"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":[0.000003271214,0.0001194982,0.00001036996,0.00008853454,0.00001009295,0.00002515431,0.000006675996,0.0007882511,0.000002125096,0.00005488686,0.9901337,0.008757442],"study_design_scores_gemma":[0.00008219213,0.0002756707,0.000008883967,0.0002378116,0.00004011887,0.000008881458,9.159745e-7,0.0002626682,0.000006531382,0.0002661279,0.9984738,0.000336404],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00005921902,0.0008844404,0.00001420141,0.3403654,0.0019097,0.0005056162,0.000125714,0.0001787016,0.655957],"genre_scores_gemma":[0.00008456247,0.0008326058,0.0004354283,0.281045,0.0001120351,0.0001066521,0.0005316508,0.00004206389,0.71681],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4979902,"threshold_uncertainty_score":0.9999661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04818500599431969,"score_gpt":0.2964158101885684,"score_spread":0.2482308041942487,"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."}}