{"id":"W4304588604","doi":"10.5194/gmd-2022-174-ac1","title":"Reply on CEC1","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; Computer science; Chlorophyll a; Fish <Actinopterygii>; Nutrient; Bloom; Bathythermograph; Workflow; Training set; Machine learning; Environmental science; Oceanography; Phytoplankton; Artificial intelligence; Ecology; Fishery; 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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006500255,0.0002604631,0.0003689128,0.00002432206,0.0001688659,0.00001703917,0.0006145536,0.0001072966,0.4856206],"category_scores_gemma":[0.0004175876,0.0001955855,0.0001634411,0.000258659,0.0001147348,0.00002392126,0.0007760167,0.0007294057,0.01141057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003720804,"about_ca_system_score_gemma":0.00001291864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009021545,"about_ca_topic_score_gemma":0.0000298481,"domain_scores_codex":[0.9976721,0.0001272376,0.0002854919,0.0007129221,0.0008628334,0.0003394433],"domain_scores_gemma":[0.9989302,0.0001073082,0.0001418165,0.0007082116,0.000003728187,0.0001087909],"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":[0.000002170686,0.0000409204,0.00001240473,0.00006184607,0.000004477072,0.00002757063,0.000003680017,0.0008902837,0.000002283844,0.00001789076,0.9893782,0.009558344],"study_design_scores_gemma":[0.00003842119,0.0001754119,0.00003101825,0.000184388,0.00002429191,0.00001302494,2.209449e-7,0.0001111083,0.000003697673,0.0002337584,0.9989384,0.0002462144],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001515975,0.0006491879,0.000005487553,0.1046472,0.001582891,0.0003178013,0.00005571813,0.0002012937,0.8923889],"genre_scores_gemma":[0.0001395099,0.0004154347,0.0004362383,0.1312251,0.0001123939,0.0000527896,0.0002312981,0.00003258721,0.8673547],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.47421,"threshold_uncertainty_score":0.9893591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04792323377388096,"score_gpt":0.2945439741124979,"score_spread":0.2466207403386169,"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."}}