{"id":"W4323276219","doi":"10.5194/egusphere-2022-938-ac3","title":"Reply on RC2","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":"McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"Swiss Polar Institute; Deutsche Forschungsgemeinschaft; European Commission; WSL-Institut für Schnee- und Lawinenforschung SLF","keywords":"Snow; Snowpack; Computer science; Segmentation; Artificial intelligence; Artificial neural network; Machine learning; Task (project management); Identification (biology); Data mining; Meteorology; Geography; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002171091,0.0008393128,0.0009640115,0.001140224,0.00313777,0.004252763,0.002780755,0.01919211,0.2506377],"category_scores_gemma":[0.03015851,0.0004954478,0.001241689,0.0008332116,0.001626619,0.003607799,0.002576835,0.01647325,0.1734546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003107558,"about_ca_system_score_gemma":0.002822267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007363521,"about_ca_topic_score_gemma":0.008780636,"domain_scores_codex":[0.9977522,0.0004235788,0.0002349271,0.0004140417,0.0007815095,0.0003936918],"domain_scores_gemma":[0.9934232,0.002105853,0.0002429741,0.0004695134,0.002822549,0.0009358344],"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":[0.00001018583,0.000003118321,0.00002972532,0.00001301091,0.000001345526,0.00005549032,0.0000113883,0.000003620293,0.00001921449,0.0003107296,0.9974618,0.002080252],"study_design_scores_gemma":[0.000008070589,0.000006007169,0.0001207185,0.00004634826,0.000002179478,0.00006271624,0.00006844585,0.00002171102,0.00006525446,0.0003637625,0.9992273,0.000007454627],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.0003762353,0.001804791,0.0004179382,0.7202752,0.205723,0.0001995495,0.001484426,0.0009116343,0.06880734],"genre_scores_gemma":[0.003683469,0.001031449,0.0002714799,0.7012753,0.04588185,0.0002441121,0.0004891524,0.0004602991,0.2466629],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7493623,"threshold_uncertainty_score":0.8384665,"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."}}